From Exploring to Building Accurate Interpretable Machine Learning Models for Decision-Making: Think Simple, not Complex

By: Yadvinder Bhuller, Health Canada; Keith O’Rourke, Health Canada

In spite of an increasing number of examples, where both simple and complex prediction models have been used for decision-making, accurate prediction continues to be pertinent for both models. The added element is that the more complex a model, the more potential it has for less uptake from novice users who may not be familiar with machine learning (ML). Complex prediction models can arise from attempts to maximize predictive accuracy without regard to how difficult it would be for an individual to anticipate the predictions from the input data. However, even with a method considered as simple as linear regression, the complexity increases as more variables and their interactions are added. At the other extreme of using numerous non-linear functions for prediction, as with Neural Nets, it is possible that the results can be too complex to understand. Such models are usually called black box prediction models. Accurate interpretable models can also vary from accurate decision trees and rule lists that are so concise they can be fully described in a sentence or two for tabular data, through modern generalized additive models (e.g., for more challenging medical records), to methods to disentangled neural nets for unstructured data such as pixels. A recent notable addition is the use of Bayesian soft complexity constrained unsupervised learning of deep layers of latent structure that is then used to construct a concise rule list with high accuracy (Gu and Dunson, 2021).

An early example, over 20 years ago, of a simple method providing as accurate prediction as more complex models is the 1998 study, by Ennis et al., of various ML learning methods to the GUSTO-I database where none of the methods could outperform a relatively simple logistic regression model. More recent accounts of complex methods, even when simple ones could suffice, are noted in the 2019 article by Rudin and Radin. The often suggested simple remedy for this unmanageable complexity is just finding ways to explain these black box models; however, those explanations can sometimes miss key information. In turn, rather than being directly connected with what is going on in the black box model, they result in being "stories" for getting concordant predictions. Given that concordance is not perfect, they can result in very misleading outcomes for many situations.

Perhaps what is needed is a wider awareness of the increasing number of techniques to build simple interpretable models from scratch that achieve high accuracy. The techniques are not simple refinements of linear or logistic regression (by rounding their coefficient to integers which loses accuracy), but involve discernment of appropriate domain-based constraints and newer methods of constrained optimization. This results in a spectrum of ease of interpretability of prediction across different applications.

Understanding where and when to be simple!

While we need to accept what we cannot understand, we should never overlook the advantages of what we can understand. For example, we may never fully understand the physical world. Nor how people think, interact, create and or decide. In ML, Geoffrey Hinton's 2018 YouTube drew attention to the fact that people are unable to explain exactly how they decide in general if something is the digit 2 or not. This fact was originally pointed out, a while ago, by Herbert Simon, and has not been seriously disputed (Erickson and Simon, 1980). However, prediction models are just abstractions and we can understand the abstractions created to represent that reality, which is complex and often beyond our direct access. So not being able to understand people is not a valid reason to dismiss desires to understand prediction models.

In essence, abstractions are diagrams or symbols that can be manipulated, in error-free ways, to discern their implications. Usually referred to as models or assumptions, they are deductive and hence can be understood in and of themselves for simply what they imply. That is, until they become too complex. For instance, triangles on the plane are understood by most, while triangles on the sphere are understood by less. Reality may always be too complex, but models that adequately represent reality for some purpose need not be. Triangles on the plane are for navigation of short distances while on the sphere, for long distances. Emphatically, it is the abstract model that is understood not necessarily the reality it attempts to represent.

However, for some reason, a persistent misconception has arisen in ML that models for accurate prediction usually need to be complex. To build upon previous examples, there remains some application areas where simple models have yet to achieve accuracy comparable to black box models. On the other hand, simple models continue to predict as accurately as any state of the art black box model and thus, the question, as noted in the 2019 article by Rudin and Radin, is: "Why Are We Using Black Box Models in AI When We Don't Need To?"

In application areas where simple models can be as accurate, not using such models has unnecessarily led to recommendations that can impact areas including societal, health, freedom, and safety. An often-discussed hypothetical choice between the accurate machine-learning-based robotic surgeon and the less-accurate human surgeon is moot once someone builds an interpretable robotic surgeon that is as accurate as any other robot. Again, it is the prediction model that is understandable, not necessarily the prediction task itself.

Simple and interpretable models?

The number of application areas where accurate simple prediction models can be built to be understood has been increasing over time. Arguably, perhaps these models should be labeled as "interpretable" ML, as they are designed from scratch to be interpretable. They are purposely constrained so that their reasoning processes are more understandable to most if not all human users. This not only makes the connection between input data and predictions almost obvious, but it is also easier to troubleshoot and modify as needed. Interpretability is in the eye of the domain and interpretability constraints can include the following:

Sparsity of the model
Monotonicity with respect to a variable
Decomposability into sub-models
An ability to perform case-based reasoning
Disentanglement of certain types of information within the model's reasoning process
Generative constraints (e.g. biological processes)
Preferences among the choice of variables
Any other type of constraint that is relevant to the domain.

Some notable examples of interpretable models include sparse logical models (such as decision trees, decision lists, and decision sets) and scoring systems which are linear classification models that require users to add, subtract, and multiply only a few small numbers to make a prediction. These models can be much easier to understand than multiple regression and logistic regression, which can be difficult to interpret. Now, the intuitive simplification of these regression models, by restricting the number of predictors and rounding the coefficients, does not provide optimal accuracy. This is just a post hoc adjustment. It is better to build in interpretability from the very start.

There is increasing understanding based on considering numerous possible prediction models in a given prediction task. The not-too-unusual observation of simple models performing well for tabular data (a collection of variables, each of which has meaning on its own) was noted over 20 years ago and was labeled the "Rashomon effect" (Breiman, 2001). Breiman posited the possibility of a large Rashomon set in many applications; that is, a multitude of models with approximately the same minimum error rate. A simple check for this is to fit a number of different ML models to the same data set. If many of these are as accurate as the most accurate (within the margin of error), then many other untried models might also be. A recent study (Semenova et al., 2019), now supports running a set of different (mostly black box) ML models to determine their relative accuracy on a given data set to predict the existence of a simple accurate interpretable model—that is, a way to quickly identify applications where it is a good bet that accurate interpretable prediction model can be developed.

What's the impact on ML from full data science life-cycle?

The trade-off between accuracy and interpretability with the first fixed data set in an application area may not hold over time. In fact, it is expected to change as either more data accumulate, the application area becomes better understood, data collection is refined or new variables are added or defined and the application area changes. In a full data science process itself, even in the first data set, one should critically assess and interpret the results and tune the processing of the data, the loss function, the evaluation metric, or anything else that is relevant. More effectively turning data into increasing knowledge about the prediction task which can then be leveraged to increase both accuracy and likely generalization. Any possible trade-off between accuracy and interpretability therefore should be evaluated in the full data science process and life cycle of ML.

The full data science and life-cycle process likely is different when using interpretable models. More input is needed from domain experts to produce an interpretable model that make sense to them. This should be seen as an advantage. For instance, it is not too unusual at a given stage to find numerous equally interpretable and accurate models. To the data scientist, there may seem little to guide the choice between these. But, when shown to domain experts, they may easily discern opportunities to improve constraints as well as indications of which ones are less likely to generalize well. All equally interpretable and accurate models are not equal in the eyes of domain experts.

Interpretable models are far more trustworthy in that they can be more readily discerned where and when they should be trusted or not and in what ways. But, how can one do this without understanding how the model works, especially for a model that is patently not trustworthy? This is especially important in cases where the underlying distribution of data changes, where it is critical to trouble shoot and modify without delays, as noted in the 2020 article by Hamamoto et al. It is arguably much more difficult to remain successful in the ML full life cycle with black box models than with interpretable models. Even for applications where interpretable models are not currently accurate enough, interpretable models can be used a tool to help debug black box models.

Misunderstanding explanations

There is now a vast and confusing literature, which conflates interpretability and explainability. In this brief blog, the degree of interpretability is taken simply as how easily the user can grasp the connection between input data and what the ML model would predict. Erasmus et al. (2020) provide a more general and philosophical view. Rudin et al. (2021) avoid trying to provide an exhaustive definition by instead providing general guiding principles to help readers avoid common, but problematic ways of thinking about interpretability. On the other hand, the term "explainability" often refers to post hoc attempts to explain a black box by using simpler 'understudy' models that predict the black box predictions. However, as noted in the Government of Canada's (GoC's) Guideline on Service and Digital, prediction is not explanation, and when they are proffered as explanations they can seriously mislead (GoC, 2021). Often this literature assumes that one would just explain a black box without consideration of whether there is an interpretable model of the same accuracy, perhaps having uncritically bought into the misconception that only models that are too complex to understand can achieve acceptable accuracy.

The increasing awareness of the dangers of these "explanations" has led one group of researchers to investigate how misunderstanding can actually be purposefully designed in; something regulators may increasingly need to worry about (Lakkaraju and Bastani, 2019). It is also not uncommon for those who routinely do black box modeling to offer explanations of these models as an alternative or even a reason to forego learning about and developing interpretable models.

Keeping it simple

Interpretable ML models are simple and can be relied upon when relying upon ML tools for decision-making. On the other hand, even interpretability is probably not needed for decisions where humans can verify or modify the decision afterwards (e.g. suggesting options). Notwithstanding the desire for simple and accurate models, it is important to note that currently interpretable MLs cannot match the accuracy of black box models in all application areas. For applications involving raw data (pixels, sound waves, etc.) black box neural networks have a current advantage over other approaches. In addition, black box models allow users to delegate responsibility for grasping implications of adopting the model. Although a necessary trade-off between accuracy and interpretability does remain in some application areas, its ubiquity remains an exaggeration and the prevalence of the trade-off may continually decrease in the future. This has created a situation in ML where opportunities to understand and reap the benefits are often overlooked. Therefore, the advantages of newer interpretable modelling techniques should be fully considered in any ML application, at a minimum to determine if adequate accuracy is achievable. Perhaps and in the end it may boil down to the fact that if simple works, then why make things more complex.

Team members: Keith O'Rourke (Pest Management Regulatory Agency), Yadvinder Bhuller (Pest Management Regulatory Agency).

Keep on machine learning...

Breiman, L. (2001). Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author). Statist. Sci. 16(3): 199-231. DOI: 10.1214/ss/1009213726

Ennis, M., Hinton, G., Naylor, D., Revow, M., and Tibshirani, R. (1998). A Comparison of Statistical Learning Methods on the Gusto Database. Statistics. Med. 17, 2501-2508. A comparison of statistical learning methods on the GUSTO database

Erasmus, A., Bruent, T.D.P., and Fisher E. (2020). What is Interpretability? Philosophy & Technology. What is Interpretability?

Ericsson, K. A., & Simon, H. A. (1980). Verbal reports as data. Psychological Review, 87(3), 215–251. Verbal reports as data.

Government of Canada. (2021). Guideline on Service and Digital. Guideline on Service and Digital. [Accessed: May 13, 2021].

Gu, Y., and Dunson, D.B. (2021). Identifying Interpretable Discrete Latent Structures from Discrete Data. arXiv:2101.10373 [stat.ME]

Hinton, G. (2018). Why Is a Two a Two? Why Is A Two A Two? With Geoffrey Hinton and David Naylor [Accessed: May 13, 2021].

Hamamoto, R., Suvarna, K., Yamada, M., Kobayashi, K., Shinkai, N., Miyake, M., Takahashi, M., Jinnai, S., Shimoyama, R., Sakai, A., Taksawa, K., Bolatkan, A., Shozu, K., Dozen, A., Machino, H., Takahashi, S., Asada, K., Komasu, M., Sese, J., and Kaneko., S. (2020). Application of Artificial Intelligence Technology in Oncology: Towards the Establishment of Precision Medicine. Cancers. 12(12), 3532; Application of Artificial Intelligence Technology in Oncology: Towards the Establishment of Precision Medicine

Lakkaraju, H., and Bastani, O. (2019). "How do I fool you?": Manipulating User Trust via Misleading Black Box Explanations. arXiv:1911.06473 [cs.AI]

Rudin, C., Chen, C., Chen, Z., Huang, H., Semenova, L., and Zhong, C. (2021). Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges. arXiv:2103.11251 [cs.LG]

Rudin, C., & Radin, J. (2019). Why Are We Using Black Box Models in AI When We Don't Need To? A Lesson From An Explainable AI Competition. Harvard Data Science Review, 1(2). Why Are We Using Black Box Models in AI When We Don't Need To? A Lesson From An Explainable AI Competition

Semenova, R., Rudin, C., and Parr, R. (2019). A study in Rashomon curves and volumes: A new perspective on generalization and model simplicity in machine learning. arXiv:1908.01755 [cs.LG]

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Date modified:: 2021-12-01

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Organic processing services:
The breakdown of organic materials through either composting or anaerobic digestion processes.

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34. Specify the names of the facilities where the non-hazardous waste was taken for processing.

Include only final destinations such as landfills, incinerators, energy from waste facilities, residual waste processors.

Exclude transfer stations unless it is the final destination for waste collected/transported by this company.

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Collection or transportation of non-hazardous recyclable materials

35. In 20xx, did this company collect or transport non-hazardous recyclable materials?

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36. Specify the names of the facilities where the recyclable materials were taken.

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37. In 20xx, did this company collect or transport organic materials?

Organic materials:
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To how many facilities was the material taken? (Maximum of 15)

38. Specify the names of the facilities where the organic material was taken for processing.

Facility

Organic material processing

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Include landfills or sites where organic materials were composted.

How many facilities? (Maximum of 15)

40. Please provide the name and owner of each processing facility.

Facility

Facility name

Facility owner

Organic material processing

41. For the specified facility, indicate which organic materials are processed at the facility.

Estimating sources of waste (garbage), recyclables and organic materials:
It is acknowledged that it is often very difficult to track the quantities of waste and recyclable materials by source unless the business or local government collects or prepares materials from only one source (e.g., a firm that collects waste only from IC&I sources).

In this survey, you are being asked to estimate the proportion of materials by source of material at three points (if applicable and known): at the facility where organic material is processed, at the facility where recyclables are prepared and at disposal. If you engage in one or more of these activities, you will be asked to estimate the proportion of waste, recyclable or organic materials from residential, non-residential and construction and demolition sources. While it is recognized that such estimates may be difficult to make, you are asked to be as accurate as possible.

Sources of materials:
Refers to the sources of generation of the waste or recyclable material. These sources are classified as residential, industrial, commercial and institutional (IC&I) and construction, renovation and demolition (CR&D). It is sometimes difficult to ascertain the source of a given material because of lack of tracking or complex collection arrangements (e.g., when collection is contracted out or when collection vehicles pick up materials from a mix of sources on their routes).

Food waste:
Includes food wastes and food scraps from households and non-residential sources such as grocery stores, restaurants, etc., destined for composting or anaerobic digestion.

Source separated organic materials (SSO):
Source separation of organics is the setting aside of organic waste materials at their point of generation (the home, office, or other place of business) by the generator. Examples of SSO materials are food scraps, soiled paper packaging such as ice cream boxes, muffin paper, flour and sugar bags, paper coffee cups and paper plates.

Leaf and yard waste:
Includes any waste collected from a yard or garden such as leaves, grass clippings, plants, tree trimmings and branches.

Forestry waste:
The debris or leftover waste from the management of forests. This would include trees, stumps, branches, etc., that were discarded.

Wood waste:
The primary constituents of wood waste are used lumber, trim, trees, branches, and other wood debris from construction and demolition clearing and grubbing activities. It includes: dimensional lumber, plywood, particle board and fibre board, crating, wood fencing, pressure treated lumber, wood shingles, wooden doors, creosoted wood products, demolition wood waste, painted wood.

Agricultural waste:
All waste materials produced as a result of agricultural activities, including, for example, residues from the application of pesticides, herbicides, fertilizers and other chemicals, wastewater, bedding material, etc.

Biosolids:
Includes solid or semisolid material obtained from treated wastewater.

Include all quantities of food waste, materials from source separated organics programs (SSO), leaf and yard waste as well as Christmas trees and pumpkins.

Leaf and yard waste

Please provide the amount and source of leaf and yard waste processed at this facility.

When precise figures are not available, please provide your best estimate.

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

If the exact source breakdown is not available, please provide your best estimate for each source.

Industrial, commercial and institutional (IC&I)

If the exact source breakdown is not available, please provide your best estimate for each source.

Construction, renovation and demolition (CR&D)

If the exact source breakdown is not available, please provide your best estimate for each source.

Food waste and SSO material

Please provide the amount and source of food waste and SSO material processed at this facility.

When precise figures are not available, please provide your best estimate.

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

If the exact source breakdown is not available, please provide your best estimate for each source.

Industrial, commercial and institutional (IC&I)

If the exact source breakdown is not available, please provide your best estimate for each source.

Construction, renovation and demolition (CR&D)

If the exact source breakdown is not available, please provide your best estimate for each source.

Forestry waste and wood waste

Please provide the amount and source of forestry waste and wood waste processed at this facility.

When precise figures are not available, please provide your best estimate.

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

If the exact source breakdown is not available, please provide your best estimate for each source.

Industrial, commercial and institutional (IC&I)

If the exact source breakdown is not available, please provide your best estimate for each source.

Construction, renovation and demolition (CR&D)

If the exact source breakdown is not available, please provide your best estimate for each source.

Agricultural waste

Please provide the amount and source of agricultural waste processed at this facility.

When precise figures are not available, please provide your best estimate.

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

If the exact source breakdown is not available, please provide your best estimate for each source.

Industrial, commercial and institutional (IC&I)

If the exact source breakdown is not available, please provide your best estimate for each source.

Construction, renovation and demolition (CR&D)

If the exact source breakdown is not available, please provide your best estimate for each source.

Biosolids

Please provide the amount and source of biosolids processed at this facility.

When precise figures are not available, please provide your best estimate.

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

If the exact source breakdown is not available, please provide your best estimate for each source.

Industrial, commercial and institutional (IC&I)

If the exact source breakdown is not available, please provide your best estimate for each source.

Construction, renovation and demolition (CR&D)

If the exact source breakdown is not available, please provide your best estimate for each source.

Other type of organic material 1

Please provide the amount and source of other type of organic material 1 processed at this facility.

When precise figures are not available, please provide your best estimate.

Specify other type of organic material 1

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

If the exact source breakdown is not available, please provide your best estimate for each source.

Industrial, commercial and institutional (IC&I)

If the exact source breakdown is not available, please provide your best estimate for each source.

Construction, renovation and demolition (CR&D)

If the exact source breakdown is not available, please provide your best estimate for each source.

Other type of organic material 2

Please provide the amount and source of other type of organic material 2 processed at this facility.

When precise figures are not available, please provide your best estimate.

Specify other type of organic material 2

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

If the exact source breakdown is not available, please provide your best estimate for each source.

Industrial, commercial and institutional (IC&I)

If the exact source breakdown is not available, please provide your best estimate for each source.

Construction, renovation and demolition (CR&D)

If the exact source breakdown is not available, please provide your best estimate for each source.

Other type of organic material 3

Please provide the amount and source of other type of organic material 3 processed at this facility.

When precise figures are not available, please provide your best estimate.

Specify other type of organic material 3

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

If the exact source breakdown is not available, please provide your best estimate for each source.

Industrial, commercial and institutional (IC&I)

If the exact source breakdown is not available, please provide your best estimate for each source.

Construction, renovation and demolition (CR&D)

If the exact source breakdown is not available, please provide your best estimate for each source.

Recycling

42. In 20xx, did this Jurisdiction/Company own or operate a facility (municipally or privately operated) that prepared materials for recycling?

e.g., material recycling facility (MRF), recycling centre, drop-off depot

Recycling:
Recycling is defined as the process whereby a recyclable material (e.g., glass, metal, plastic, paper) is diverted from the waste stream in order to be remanufactured into a new product, or is used as a raw material substitute.

Recycling centre/drop off depot:
A facility or site where the public can bring materials for recycling or re-use. In some cases, household hazardous waste or special waste is accepted at these sites.

Material Recycling Facility (MRF):
A facility where materials that are collected for recycling are prepared or processed. The preparation or processing can include sorting, baling, cleaning, crushing, volume reduction and storing until shipment.

How many facilities? (Maximum of 15)

43. Please provide the name and owner of each recycling facility.

Facility

Facility name

Facility owner

44. For the specified facility, indicate your best estimate of the sources of recycled materials.

Ferrous metals:
These are metals which contain iron. They may have small amounts of other metals or other elements added, to yield specific properties. All ferrous metals are magnetic and give little resistance to corrosion. Steel is an example of a ferrous metal. The recycling of ferrous metals include but is not limited to the processing of tin/steel cans, strapping, as well as the extraction of metals from appliances.

Scrap metal:
Any metal cutting or reject of a manufacturing operation, which may be suitable for recycling.

Textiles:
Material composed of natural or synthetic fibers, including any combination of animal derived material such as wool or silk, plant-derived material such as linen and cotton, and synthetic material such as polyester or nylon (e.g., towels, shoes, purses, clothing, curtains and carpets).

White goods:
Includes metal items such as: stoves, fridges, freezers, air conditioners, dehumidifiers, washers, dryers, hot water tanks, metal sinks, microwaves, and various other metal items.

Plastics:
PET (1): Polyethylene Terephthalate, commonly abbreviated as PET or PETE, is a polymer resin of the polyester family. PET is identified by the number 1 recycling symbol. Commonly recyclable PET materials include 2 litre soda bottles, water bottles, cooking oil bottles, peanut butter jars.

HDPE (2): High Density Polyethylene is a polyethylene thermoplastic made from petroleum. HDPE is identified by the number 2 recycling symbol. Some commonly recycled HDPE materials include detergent bottles, milk jugs, and grocery bags.

All other plastics (3-7): Polyvinyl Chloride - PVC (3), Low Density Polyethylene - LDPE (4), Polypropylene - PP (5), Polystyrene - PS (6), Other (7). Common uses: (3) plastic pipes, outdoor furniture, shrink wrap, water bottles, (4) dry cleaning bags, produce bags, trash can liners, (5) aerosol caps, drinking straws, (6) packaging pellets, Styrofoam cups, (7) food containers.

Electronics:
Electronics are items that function through the use of electricity and/or batteries. Also included are items that have a circuit board but do not necessarily require electricity from an outlet (such as telecommunication equipment). Examples are personal computers, laptops, monitors, peripheral devices (printers, scanners, etc.), telephones, cell phones, facsimile machines, stereos, portable music players and children's toys containing electronic components.

Only count quantities once. Exclude organic materials reported in question 41.

Newsprint and magazines

Quantity of materials

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

Industrial, commercial and institutional (IC&I)

Construction, renovation and demolition (CR&D)

Corrugated cardboard

Quantity of materials

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

Industrial, commercial and institutional (IC&I)

Construction, renovation and demolition (CR&D)

Mixed paper fibre and boxboard

Quantity of materials

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

Industrial, commercial and institutional (IC&I)

Construction, renovation and demolition (CR&D)

Glass

Quantity of materials

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

Industrial, commercial and institutional (IC&I)

Construction, renovation and demolition (CR&D)

Ferrous metals

Include ferrous scrap metal.

Quantity of materials

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

Industrial, commercial and institutional (IC&I)

Construction, renovation and demolition (CR&D)

White goods

e.g., household appliances

Quantity of materials

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

Industrial, commercial and institutional (IC&I)

Construction, renovation and demolition (CR&D)

Aluminum

Quantity of materials

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

Industrial, commercial and institutional (IC&I)

Construction, renovation and demolition (CR&D)

Copper

Quantity of materials

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

Industrial, commercial and institutional (IC&I)

Construction, renovation and demolition (CR&D)

Mixed metals

Quantity of materials

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

Industrial, commercial and institutional (IC&I)

Construction, renovation and demolition (CR&D)

Plastics

Quantity of materials

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

Industrial, commercial and institutional (IC&I)

Construction, renovation and demolition (CR&D)

Aseptic containers and tetra packs

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

Industrial, commercial and institutional (IC&I)

Construction, renovation and demolition (CR&D)

Gable top containers

e.g., milk cartons

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

Industrial, commercial and institutional (IC&I)

Construction, renovation and demolition (CR&D)

Electronics

Quantity of materials

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

Industrial, commercial and institutional (IC&I)

Construction, renovation and demolition (CR&D)

Tires

Quantity of materials

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

Industrial, commercial and institutional (IC&I)

Construction, renovation and demolition (CR&D)

Construction, renovation and demolition (CR&D) material

Quantity of materials

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

Industrial, commercial and institutional (IC&I)

Construction, renovation and demolition (CR&D)

Textiles

Quantity of materials

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

Industrial, commercial and institutional (IC&I)

Construction, renovation and demolition (CR&D)

Other 1

Specify type of material

Quantity of materials

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

Industrial, commercial and institutional (IC&I)

Construction, renovation and demolition (CR&D)

Other 2

Specify type of material

Quantity of materials

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other
Specify other unit of measure

Residential

Industrial, commercial and institutional (IC&I)

Construction, renovation and demolition (CR&D)

Other 3

Specify type of material

Quantity of materials

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Residential

Industrial, commercial and institutional (IC&I)

Construction, renovation and demolition (CR&D)

Transfer stations

45. In 20xx, did this Jurisdiction/Company own or operate a transfer station for non-hazardous waste?

How many transfer stations? (Maximum of 15)

46. Please provide the following information for the transfer stations reported in Question 45.

Transfer station

Station name

Owner of this facility

Type of facility

Transfer station

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Was a weigh scale present?

Quantity of waste managed through this transfer station

Residential

Industrial, commercial and institutional (IC&I)

Construction, renovation and demolition (CR&D)

Waste (garbage) disposal or processing

47. Did this Jurisdiction/Company own or operate a facility where waste was disposed or processed in 20xx?

Include:

all types of landfills, e.g., sanitary, stabilized, bioreactor
incineration or thermal treatment, e.g., energy from waste, gasification
residual waste processing, e.g., conversion of non-recyclable waste to alternative fuel source.

How many facilities? (Maximum of 15)

48. Please provide the following information for the facilities reported in Question 47.

Facility

Facility name

Owner of this facility

Type of facility

Landfill
Processor
Incinerator

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Was a weigh scale present?

Quantity of waste disposed or processed in this facility

Residential

Industrial, commercial and institutional (IC&I)

Construction, renovation and demolition (CR&D)

Landfills

49. For the landfills reported in question 48, were any of the following materials received?

Bottom ash:
The residue ash that remains after the incineration of a waste material.

Contaminated soil:
Soils containing materials that, by their nature, require controlled disposal.

Clean fill:
Uncontaminated inert solid material including soil, rock, stone, dredged material, used asphalt, and brick, block or concrete. The soil is considered "clean" because it has not been contaminated or affected, for example by a spill or release of toxic materials.

Bottom ash from sewage sludge or solid waste incineration

Report the quantity of bottom ash from sewage sludge or solid waste incineration.

Quantity received at landfill

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Contaminated soil

Report the quantity of contaminated soil.

Quantity received at landfill

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Clean fill

Report the quantity of clean fill.

Quantity received at landfill

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other
Specify other unit of measure

Household hazardous or special waste and waste reduction

50. In 20xx, did this jurisdiction, in cooperation or conjunction with another jurisdiction or solely, administer a program to collect household hazardous and special waste?

Household hazardous/special waste (HHW):
Materials generated by residential households that cannot be collected in standard residential recycling programs and present a risk to municipal waste management systems because of their hazardous and/or toxic nature. This includes solid or liquid materials, or containers holding gases which have outlived their usefulness. This waste may be flammable, corrosive, explosive or toxic and therefore should not be disposed in landfills or sewage systems.

Waste reduction

51. In 20xx, did this jurisdiction conduct any of the following programs to encourage the reduction of waste?

Select all that apply.

Bag limits
Distribution of backyard composters (subsidized)
Reduced garbage collection frequency
e.g., every two weeks
User fees or bag tags
Clear bag program for garbage
Other 1
- Specify program 1
Other 2
- Specify program 2
Other 3
- Specify program 3
Other 4
- Specify program 4
OR
None of the above

Exports of waste for disposal or processing

52. In 20xx, did this Jurisdiction/Company own or operate a facility in operating province that transported or exported non-hazardous waste for disposal or processing to another province or territory or to another country?

Include direct shipments and shipments from transfer stations.

How many facilities? (Maximum of 15)

53. Provide the names of facilities handling non-hazardous waste for the purpose of exporting to another province or territory or to another country.

Facility

Facility name

Facility operator

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other
Specify other unit of measure

Quantity of waste exported to another province or territory

Quantity of waste exported to the United States

Quantity of waste exported to countries other than the United States

Imports of waste for disposal or processing

54. In 20xx, was non-hazardous waste from outside this province or territory disposed or processed in this Jurisdiction/Company 's facility/facilities in operating province ?

e.g., landfill facility, incinerator and energy from waste facility, or residual waste processing facility

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

55. Report the quantity of non-hazardous waste disposed or processed in operating province from other provinces or territories or from the United States.

Quantity of non-hazardous waste received from other provinces or territories in

Quantity of non-hazardous waste received from the United States in

Exports of recyclable materials

56. In 20xx, did this Jurisdiction/Company own or operate a facility in operating province that transported or exported recyclable materials to a material recycling facility (MRF) in another province or territory or in another country?

Exclude exports of recyclable materials to end markets in other provinces or the United States.

How many facilities? (Maximum of 15)

57. Provide the names of facilities handling recyclable materials for the purpose of exporting to another province or territory or to another country.

Facility

Facility name

Facility operator

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other
Specify other unit of measure

Quantity of recyclables exported to another province or territory

Quantity of recyclables exported to the United States

Quantity of recyclables exported to countries other than the United States

Imports of recyclable materials

58. In 20xx, were recyclable materials from outside operating province processed in this Jurisdiction/Company's material recycling facility/facilities (MRF)?

Unit of measure

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other
Specify other unit of measure

59. Report the quantity of recyclable materials processed from other provinces or territories or from the United States.

Quantity of recyclables processed from other provinces or territories in

Quantity of recyclables processed from the United States in

Employment information

60. In 20xx, what was the average number of full-time (30 or more hours per week) and part-time (less than 30 hours per week) employees in operating province whose primary function is to work on the waste management activities of this Jurisdiction/Company ?

Exclude full-time equivalents for part-time employees, contract employees or sub-contractor's employees.

Average number of full-time employees in 20xx

Average number of part-time employees in 20xx

Waste management services - Business

61. Did this company provide waste management services in more than one province or territory in 20xx?

62. Indicate the other provinces or territories in which this company provides waste management services.

Select all that apply.

Alberta
British Columbia
Manitoba
New Brunswick
Newfoundland and Labrador
Northwest Territories
Nova Scotia
Nunavut
Ontario
Prince Edward Island
Québec
Saskatchewan
Yukon

Attach files

63. If you wish to report or submit additional documents using a separate attachment, please follow the instructions below.

Steps to attach a document

Step 1. Press the Attach files button

Step 2. Choose the file to attach

Step 3. Double click on the file to attach

To attach more than one document, repeat steps 1 to 3.

The name and size of each file attached will be displayed on the page.

Note: Each file attached must not exceed 5 MB and for the entire questionnaire, the total size must not exceed 50 MB.

Waste management and materials recovery

64. Is this business involved in the purchase or resale of metal (ferrous and non-ferrous), glass, plastic or other material?

Ferrous metals are metals containing iron. They may contain other metals to yield specific properties, are magnetic and subject to corrosion. Steel is an example of a ferrous metal.

Non-ferrous metals include non-iron containing metals, such as copper and aluminum.

65. Which of the following materials were sold by this business in 20xx?

Include materials recovered from items such as automobiles, household appliances and furniture, construction materials, etc.

Non-ferrous metals:
Non-ferrous metals include non-iron containing metals, such as copper and aluminum.

Plastics:PET (1):
Polyethylene Terephthalate, commonly abbreviated as PET or PETE, is a polymer resin of the polyester family. PET is identified by the number 1 recycling symbol. Commonly recyclable PET materials include 2 litre soda bottles, water bottles, cooking oil bottles, peanut butter jars.

HDPE (2):
High Density Polyethylene is a polyethylene thermoplastic made from petroleum. HDPE is identified by the number 2 recycling symbol. Some commonly recycled HDPE materials include detergent bottles, milk jugs, and grocery bags.

All others plastics (3-7):
Polyvinyl Chloride – PVC (3), Low Density Polyethylene – LDPE (4), Polypropylene – PP (5), Polystyrene – PS (6), Other (7). Common uses: (3) plastic pipes, outdoor furniture, shrink wrap, water bottles, (4) dry cleaning bags, produce bags, trash can liners, (5) aerosol caps, drinking straws, (6) packaging pellets, Styrofoam cups, (7) food containers.

Include materials recovered from items such as automobiles, household appliances and furniture, construction materials, etc.

Select all that apply.

Ferrous Metal

Please indicate the amount of ferrous metal prepared for market and sold by this facility in 20xx.

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Non-ferrous metals

Please indicate the amount of non-ferrous metal prepared for market and sold by this facility in #{ReferencePeriod}.

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Glass (include automotive)

Please indicate the amount of glass prepared for market and sold by this facility in 20xx.

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Plastic

Please indicate the amount of plastic prepared for market and sold by this facility in 20xx.

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Other material

Please indicate the amount of other material prepared for market and sold by this facility in 20xx.

Specify other material

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Waste management and materials recovery

66. What does your company do with its waste?

All of the waste is picked up by a waste management company

Some of the waste is picked up by a waste management company, but a portion is picked up by or sent to a third-party for recycling/recovery

May include: paper products sent to a pulp and paper processor; bottle return programs; metal brought to a scrap dealer, etc.

A third-party picks up the waste for recycling/recovery
i.e., a waste management company does not handle our waste

Important: These questions pertain to the portion of your company's waste that is not sent to or picked up by a waste management company.

Please include waste materials that are picked up by or sent directly to a third-party establishment for recovery/recycling.

Examples might include: paper products sent to a pulp and paper processor; bottle return programs; metal sent to a scrap dealer, etc.

67. Which of the following materials were picked up by or sent to a third-party in 20xx?

Plastics: PET (1):
Polyethylene Terephthalate, commonly abbreviated as PET or PETE, is a polymer resin of the polyester family. PET is identified by the number 1 recycling symbol. Commonly recyclable PET materials include 2 litre soda bottles, water bottles, cooking oil bottles, peanut butter jars.

HDPE (2):
High Density Polyethylene is a polyethylene thermoplastic made from petroleum. HDPE is identified by the number 2 recycling symbol. Some commonly recycled HDPE materials include detergent bottles, milk jugs, and grocery bags.

Food waste: Includes food wastes and food scraps from households and non-residential sources such as grocery stores, restaurants, etc., destined for composting or anaerobic digestion.

Non-ferrous metals:
Non-ferrous metals include non-iron containing metals, such as copper and aluminum.

Appliances (White goods): Includes metal items such as: stoves, fridges, freezers, air conditioners, dehumidifiers, washers, dryers, hot water tanks, metal sinks, microwaves, and various other metal items.

A third-party could include independent contractors, scrap metal company, etc.

Select all that apply.

Paper products

e.g., paper, mixed paper, cardboard, boxboard, etc.

Please provide the amount of paper products picked up by or sent to a third-party processor in 20xx.

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Destination (e.g., company name)

Plastic

e.g., products and packaging made of plastic that are sent for recovery/recycling

Please provide the amount of plastic picked up by or sent to a third-party processor in 20xx.

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Destination (e.g., company name)

Food waste

Please provide the amount of food waste picked up by or sent to a third-party processor in 20xx.

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Destination (e.g., company name)

Glass

Please provide the amount of glass picked up by or sent to a third-party processor in 20xx.

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Destination (e.g., company name)

Metal

Include ferrous and non-ferrous metals

Please provide the amount of metal picked up by or sent to a third-party processor in 20xx.

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Destination (e.g., company name)

Appliances

Please provide the amount of appliances picked up by or sent to a third-party processor in 20xx.

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Destination (e.g., company name)

Other material

Please provide the amount of other material picked up by or sent to a third-party processor in 20xx.

Specify other material

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Destination (e.g., company name)

Waste management and materials recovery

68. Does this establishment collect material as part of a take-it back program (e.g., used tank return, used/old electronic products)?

Include deposit-return programs and materials returned through Extended Producer Responsibility (EPR) programs.

Definition: Extended Producer Responsibility (EPR) is a program in which manufacturers of products are responsible for managing the end-of-life recycling/disposal of their products, post consumer use.

69. Which of the following materials did your company collect as part of a take-it back program in 20xx?

Appliances (White goods):
Includes metal items such as: stoves, fridges, freezers, air conditioners, dehumidifiers, washers, dryers, hot water tanks, metal sinks, microwaves, and various other metal items.

Select all that apply.

Electronic waste

Please indicate the amount of electronic waste your company collected in 20xx.

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Tires

Please indicate the amount of tires your company collected in 20xx.

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Appliances

Include items such as washers, dryers, stoves, fridges, etc.

Please indicate the amount of appliances your company collected in 20xx.

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Glass

Please indicate the amount of glass your company collected in 20xx.

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

Other material

Please indicate the amount of other material your company collected in 20xx.

Specify other material

Quantity of materials

Unit of measure (UOM)

Note: If the UOM is not listed, select "Other specify".

Metric tonnes
Kilograms
Pounds
Cubic meters
Cubic yards
Short ton
Truck load
Bale
Units or items
Other specify
Specify other unit of measure

An image is worth a thousand words: let your dashboard speak for you!

By: Chatana Mandava, Statistics Canada

A dashboard is a visual display of the most important information needed to achieve one or more objectives; information is consolidated and arranged on a single screen so that it can be monitored at a glance. Dashboards play a major role in the data science field as they are one of the most powerful ways to summarize results and communicate them to users. Statistics Canada's analysts often spend their time searching for information from the data provided or deriving insights from the data manually. Presenting a user-friendly and interactive dashboards reduces the workload for analysts as they can get the relevant information just by using filters. Dashboards are a powerful way of representing information that can be used to observe trends and monitor the performance of models to facilitate decision-making within an organization. Presented effectively, dashboards increase the productivity of users by reducing the landscape of information that needs to be parsed. Presented ineffectively, they can make finding the right information a daunting endeavour.

There are multiple tools like Tableau, Power BI, Dash Plotly and Kibana that can be used to build an effective and interactive dashboard. The choice of tool is dependent on multiple factors like type of data (e.g. text, numerical), size of data, parameters and also requirements of users. This article explores examples of two different problem statements and two different dashboards built based on their requirements.

Dashboards using Elasticsearch and Kibana

For a recent project, data scientists at Statistics Canada were tasked with building a dashboard to visualize COVID-19-related news articles and to be able to filter articles based on company name, source name, extraction source name, date, and a few important keywords such as COVID, Personal Protective Equipment, etc. The data extracted to solve this problem were text data. Millions of news articles were extracted through web scraping and various other means. Multiple machine learning and deep learning models such as SVM (Support vector Machines) and BERT (Bidirectional encoder representation from transformers) were applied to classify the news articles. The optimal way to display the consolidated results was to build an interactive dashboard. For this project, a Kibana dashboard was built to display all the news articles and visual representations of the output.

Elasticsearch is a search engine based on the Lucene Library. Elasticsearch allows the storage of huge volumes of data, and allows users to search through the data quickly and display the results in milliseconds. Instead of searching the text directly, it searches through an index and delivers results within a short amount of time. Kibana is a visualization and management tool for Elasticsearch. Given the objective of the project, Kibana was chosen as the appropriate tool. There are many interesting features in Kibana that allow users to build histograms, pie charts, bar charts, maps and so forth. The interactivity is automatically handled in Kibana. There are many other visualization tools (like Vega or Timelion) which can help create aggregate-based visualizations. Another interesting feature in Kibana is the ability to customize visualizations. The new Vega component allows users to create a variety of data visualizations available from the Vega library. The data can be ingested into Elasticsearch with the help of a Python library. The main objective of using the Elasticsearch Python library is to access news articles and store them in Elasticsearch for searching and analytics purpose. The data are scraped and ingested into Elasticsearch by creating a strict schema or mapping to make sure the data are being indexed in the correct format and type. Querying can be performed once the record is indexed.

A Kibana dashboard to provide multiple interfaces for interrogating data. This example demonstrates the use of a word cloud, a time series chart to show the number of articles extracted in a given time period, and tables to expose data elements within the — Description - Figure 1
An example Kibana dashboard with multiple filters for analysts to quickly find items of interest.

The inbuilt options in Kibana Dashboard were utilized to build an interactive dashboard from the news articles. Over a period of approximately 10 days, a time series chart was built to analyze the total number of articles that were extracted during the period of time. This is an interactive time series plot that allows users to click on any year and the articles are filtered accordingly. The table option was used to visualize the title, body, snippet, extraction source, company name, source name and media name of the news articles. All the required filtrations were included in the dashboard, along with some aggregation visualizations. A few other features, such as word clouds, were also included which helped the analysts to understand the important words in those news articles and filter the required articles based on those words. These words change when filters are applied and new sets of words appear as per the sub-selected articles. One of the features allows users to save the results in a CSV file in case the analyst needs to incorporate other tools for further analysis. Users can also share the dashboard with others by sending them a URL.

The index patterns feature in Kibana helps to modify the index patterns and to update the index pattern field accordingly. An index pattern allows you to define properties of the field. For example, when the data are ingested into the database few fields will become searchable and some fields will be aggregable. The index pattern allows users to enable these features for all the fields. In the above problem case there is a field which contains the URL of the articles. When ingested this URL field format changed to Text. The format was modified to a clickable URL with the help of an index pattern.

Dash Plotly

In another example of the uses of dashboards, a second project at Statistics Canada set out to detect events from news articles. Working with users over a 35 day period, the final results were displayed in a dashboard built using Dash Plotly. Dash is an open source tool developed by Plotly for building machine learning and data science web apps. It allows users to insert various widgets, choosing dispositions and style as Dash's layout is HTML-based.

This dashboard also included a table that displays news articles, a summary of other articles, interactive buttons to move to next and previous article, a time series graph and a drop-down menu to filter articles based on company name, date, and division. Dash doesn't include the same number of inbuilt features as Kibana. It is meant to provide a lower level of functionality for building custom web applications. Through Dash Plotly, users can highlight the location, organization, date and time in the news articles. The entire script for the dashboard is written in Python, meaning special consideration needs to be given if it is to be shared outside your organization.

Pick the approach based on end-user needs

While this article examined dashboards built using Kibana and Dash Plotly, there are many other interactive dashboards that can be built using various tools. Both of the projects discussed leveraged cloud-based systems, but desktop tools also exist that can be connected to systems with less demanding requirements. Both Kibana and Plotly provide flexible systems, but they integrate into workflows in different ways. Elasticsearch is heavily focused on high performance text indexing and searching, making it a good choice for interaction with large amounts of text data. Dash Plotly incorporates all the power and convenience of Pandas for manipulating the data. Which tool you choose to use depends heavily on the context and requirements of the project and the needs of the end-users.

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Date modified:: 2021-12-01

Responsible use of automated decision systems in the federal government

By: Benoit Deshaies, Treasury Board of Canada Secretariat; Dawn Hall, Treasury Board of Canada Secretariat

Automated decision systems are computer systems that automate part or all of an administrative decision-making process. These technologies have foundations in statistics and computer science, and can include techniques such as predictive analysis and machine learning.

The Treasury Board Directive on Automated Decision-Making ("the Directive") is a mandatory policy instrument which applies to most federal government institutions, with the notable exception of the Canada Revenue Agency (CRA). It does not apply to other levels of government such as provincial or municipal governments. The Directive supports the Treasury Board Policy on Service and Digital and sets out requirements that must be met by federal institutions to ensure the responsible and ethical use of automated decision systems, including those using artificial intelligence (AI).

Data scientists play an important role in assessing data quality and building models to support automated decision systems. An understanding of when the Directive applies and how to meet its requirements can support the ethical and responsible use of these systems. In particular, the explanation requirement and the guidance (Guidance on Service and Digital, section 4.5.3.) from the Treasury Board of Canada Secretariat (TBS) on model selection are of high relevance to data scientists.

Potential issues with automated decisions

The use of automated decision systems can have benefits and risks for federal institutions. Bias and lack of explainability are two areas where issues can arise.

Bias

In recent years, data scientists have become increasingly aware of the "bias" of certain automated decision systems, which can result in discrimination. Data-driven analytics and machine learning can accurately capture both the desirable and undesirable outcomes of the past, and project them forward. Algorithms based on historic data can in some cases amplify race, class, gender and other inequalities of the past. As well, algorithms trained on datasets with a lack of, or disproportionate, representation can impact the accuracy of the systems. For example, many facial recognition systems don't work equally well, depending on the skin, colour or gender of the person^{Footnote 1}, ^{Footnote 2}. Another common example is a model to support recruitment developed by Amazon which disproportionately favored male applicants. The underlying issue was identified to be that the model had been trained using the résumés of previous tech applicants to Amazon, who were predominantly men^{Footnote 3},^{Footnote 4}.

Lack of explainability

Another potential issue with automated systems is when one cannot explain how the system arrived at its predictions or classifications. In particular, it can become difficult to produce an easily understood explanation when the systems grow in complexity, such as when neural networks are used^{Footnote 5}. In the context of the federal government, being able to explain how administrative decisions are made is critical. Individuals denied services or benefits have a right to a reasonable and understandable explanation from the government, which goes beyond indicating that it was a decision made by a computer. A strong illustration of this problem was seen when an algorithm started reducing the amount of medical care received by patients, leading to consequences that affected peoples' health and well-being. In this case, users of the system could not explain why this reduction occurred^{Footnote 6}.

Objectives of the Directive

The issues described above are mitigated in conventional ("human") decision-making by laws. The Canadian Charter of Rights and Freedoms defines equality rights and precludes discrimination. Core administrative law principles of transparency, accountability, legality and procedural fairness define how decisions need to be made and what explanations must be provided to those impacted. The Directive interprets these principles and protections in the context of digital solutions making or recommending decisions.

The Directive also aims to ensure that automated decision systems are deployed in a manner that reduces risks to Canadians and federal institutions, and leads to more efficient, accurate, consistent and interpretable decisions. It does so by requiring an assessment of the impacts of algorithms, quality assurance measures for the data and the algorithm, and proactive disclosures about how and where algorithms are being used, to support transparency.

Scope of the Directive

The Directive applies to automated decision systems used for decisions that impact the legal rights, privileges or interests of individuals or businesses outside of the government—for example, the eligibility to receive benefits, or who will be the subject of an audit. The Directive came into force on April 1, 2019, and applies to systems procured or developed after April 1, 2020. Existing systems are not required to comply, unless an automated decision is added after this date.

Awareness of the scope and applicability of the Directive can enable data scientists and their supervisors to support their organization in implementing the requirements of the Directive to enable the ethical and responsible use of these systems.

For example, it is important to note that the Directive applies to the use of any technology, not only artificial intelligence or machine learning. This includes digital systems making or recommending decisions, irrelevant of the technology used. Systems automating calculations or implementing criteria that do not require or replace judgement could be excluded, if what they are automating is completely defined in laws or regulations, such as limiting the eligibility of a program to those 18 years or above in age. However, seemingly simple systems could be in scope if they are designed to replace or automate judgement. For example, a system which supports the detection of potential fraud by selecting targets for inspections using simple indicators, such as a person making deposits in three or more different financial institutions in a given week (a judgement of "suspicious behavior"), could be in scope.

The Directive applies to systems that make, or assist in making, recommendations or decisions. Having a person make the final decision does not remove the need to comply with the Directive. For example, systems that provide information to officers who make the final decisions could be in scope. There are multiple ways in which algorithms can make, or assist in making, recommendations or decisions. The list below illustrates some of these, reflecting how automating aspects of the fact finding or analysis process may influence subsequent decisions.

Some of the ways in which algorithms can support and influence decision-making processes:

present relevant information to the decision-maker
alert the decision-maker of unusual conditions
present information from other sources ("data matching")
provide assessments, for example by generating scores, predictions or classifications
recommend one or multiple options to the decision-maker
make partial or intermediate decisions as part of a decision-making process
make the final decision.

Requirements of the Directive

The following requirements of the Directive are foundational in enabling the ethical and responsible use of automated decision systems. Each section includes a brief description of the requirement and relevant examples that can enable their implementation.

Algorithmic Impact Assessment

It is important to understand and measure the impact of using automated decision systems. The Algorithmic Impact Assessment Tool (AIA) is designed to help federal institutions better understand and manage the risks associated with automated decision systems. Completing an AIA before production and when system functionality changes is required by the Directive.

The AIA provides the impact level for a system based on the responses federal institutions provide to a number of risk and mitigation questions, many of which are of high relevance to data scientists and their supervisors. This includes questions on potential risks related to the algorithm, the decision, and the source and type of data, as well as mitigation efforts such as consultation and the identification of processes and procedures in place to assess data quality.

The output of the AIA assigns an impact level ranging from Level I (little impact) to Level IV (very high impact). For example, a simple system deciding on the eligibility of receiving a $2 rebate for purchasing an energy-efficient light bulb might be Level I, whereas a complex neural network incorporating multiple data sources deciding to grant a prisoner parole would be a Level IV. The impact assessment is multi-faceted and was established through consultations with academia, civil society and other public institutions.

The impact level determined by the AIA supports the Directive in matching the appropriate requirements with the type of application being designed. While some of the Directive requirements apply to all systems, others vary according to the impact level. This ensures that the requirements are proportional to the potential impact of the system. For instance, at impact Level I decisions can be fully automated, whereas at Level IV the final decision must be made by a person. This supports the Directive requirements on "Ensuring human intervention" for more impactful decisions.

Demonstrates the flow an AI project will take, starting with the Algorithmic Impact Assessment to measure the impact level and determine the requirements outlined in Appendix C of the Directive. — Description - Figure 1
The impact level calculated by the AIA determines the scaled requirements of the Directive.

Finally, the Directive requires publication of the final results of the AIA on the open government portal—an important transparency measure. This serves as a registry of automated decision systems in use in government, informs the public of when algorithms are used, and provides basic details about their design and the mitigation measures that were taken to reduce negative outcomes.

Transparency

The Directive includes a number of requirements aimed at ensuring that the use of automated decision systems by federal institutions is transparent. As mentioned above, publication of the AIA on the open government portal serves as a transparency measure. As clients will rarely consult this portal before accessing services, the Directive also requires that a notice of automation be provided to clients through all service delivery channels in use (Internet, in person, mail or telephone).

Another requirement which supports transparency, and is of particular relevance to data scientists, is the requirement to provide "a meaningful explanation to affected individuals of how and why the decision was made". This article presented how certain complex algorithms will be more difficult to explain, making this requirement more difficult to meet. In its guidance, TBS says to favor "easily interpretable models" and "the simplest model that will provide the performance, accuracy, interpretability and lack of bias required", distinguishing between interpretability and explainability (Guideline on Service and Digital, section 4.5.3.). This guidance is aligned with the work of others on the importance of interpretable models such as Rudin^{Footnote 7} and Molnar^{Footnote 8}.

Likewise, when the source code is owned by the Government of Canada, it needs to be released as open source, where possible. In the case of proprietary systems, the Directive requires that all versions of the software are safeguarded to retain the right to access and test the software and to authorize external parties to review and audit these components as necessary.

Beyond the publication of source code, additional transparency measures support the communication of the use of automated decision systems to a broad audience. Specifically, at impact levels III and IV, the Directive requires the publication of a plain language description of how the system works, how it supports the decision and the results of any reviews or audits. The latter could include the results of Gender-based Analysis Plus, Privacy Impact Assessments, and peer reviews, among others.

Quality assurance

Quality assurance plays a critical role in the development and engineering of any system. The Directive includes a requirement for testing before production, which is a standard quality assurance measure. However, given the unique nature of automated decision systems, the Directive also requires development of processes to test data for unintended biases that may unfairly impact the outcomes, and ensure that the data are relevant, accurate and up-to-date.

Quality assurance efforts should continue after the system is deployed. Operating the system needs to include processes to monitor the outcomes on a scheduled basis to safeguard against unintentional outcomes. The frequency of those verifications could depend on a number of factors, such as the impact and volume of decisions, and the design of the system. Learning systems that are frequently retrained may require more intense monitoring.

There is also direct human involvement in quality assurance, such as the need to consult legal services, provide human oversight of decisions with higher levels of impacts (often referred to as having a "human-in-the-loop"), and ensure sufficient training for all employees developing, operating and using the system.

Finally, the Directive requires a peer review from a qualified third party. The goal of this review is to validate the algorithmic impact assessment, the quality of the system, the appropriateness of the quality assurance and risk mitigation measures, and to identify the residual risk of operating the system. The peer review report should be considered by officials before making the decision to operate the system. A collaboration between TBS, the Canada School of Public Service and the University of Ottawa resulted in a guide proposing best practices for this activity^{Footnote 9}.

Conclusion

The automation of service delivery by the government can have profound and far reaching impacts, both positive and negative. The adoption of data-driven technologies presents a unique opportunity to review and address past biases and inequalities, to build a more inclusive and fair society. Data scientists have also seen that automated decision systems can present some issues with bias and lack of explainability. The Treasury Board Directive on Automated Decision-Making provides a comprehensive set of requirements that can serve as the basic framework for the responsible automation of services and for preserving the basic protection of law in the digital world. In administrative law, the degree of procedural fairness for any given decision-making process increases or decreases with the significance of that decision. Likewise, the requirements of the Directive scale according to the impact level calculated by the algorithmic impact assessment.

Data scientists of the federal public service can play a leadership role in this transformation of government. By supporting the Directive in ensuring that decisions are efficient, accurate, consistent and interpretable, data scientists have the opportunity to identify ways to improve and optimize service and program delivery. Canadians also need data scientists to lead efforts to identify undesired biases in data, and support the responsible adoption of automation by building interpretable models, providing the transparency, fairness and explainability required.

Note: Stay tuned for an upcoming article on Statistics Canada’s Responsible Machine Learning Framework. The Data Science Network welcomes submissions for additional articles on this topic. Don’t hesitate to send us your article!

Team members
Benoit Deshaies, Dawn Hall

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Date modified:: 2021-12-01

Monthly Survey of Manufacturing: National Level CVs by Characteristic - April 2021

National Level CVs by Characteristic
Month	Sales of goods manufactured	Raw materials and components inventories	Goods / work in process inventories	Finished goods manufactured inventories	Unfilled Orders
Month	%
April 2020	0.87	0.99	1.20	1.41	1.10
May 2020	0.80	1.04	1.13	1.37	1.06
June 2020	0.69	1.05	1.19	1.38	1.06
July 2020	0.69	1.02	1.15	1.43	1.10
August 2020	0.64	1.05	1.23	1.50	1.20
September 2020	0.67	1.05	1.22	1.54	1.20
October 2020	0.69	1.02	1.18	1.53	1.15
November 2020	0.72	1.09	1.20	1.46	1.33
December 2020	0.69	1.04	1.18	1.46	1.37
January 2021	0.80	1.01	1.22	1.59	1.49
February 2021	0.76	1.01	1.49	1.68	1.36
March 2021	0.70	1.03	1.43	1.70	1.43
April 2021	0.72	1.06	1.52	1.70	1.40

Statistics Canada's publishing initiatives

Canadians are increasingly using mobile devices, such as smartphones and tablets, to access Government of Canada information and services.

To keep pace with this demand and to better serve users, Statistics Canada is now in the early stages of developing a mobile application to modernize the way data are published.

This consultation helped us gain insight on users' online behaviours and preferences and will support the agency's objectives to provide information in multiple formats and from multiple access points.

Respondent profile

When asked which user group they identify with, 49% of respondents identified in the program, policy and advocacy group, 18% as the education and research group, 18% as members of the general population, 10% as businesses, 7% as data services, 6% as other, and 1% as media.

Results

The 1004 responses to the consultation revealed that 44% of users read the news online in the early morning (5:00am to 8:30am); 44% in the morning (8:30am to 12:00pm); 18% in the afternoon (12:00pm to 5:00pm); 30% in the early evening (5:00pm to 9:00pm); 24% in the evening (9:00pm to midnight); and 3% overnight (midnight to 5:00am).

Furthermore, it was shown that the most important features or functionalities if Statistics Canada had a mobile application would be to ability to search for content (74%), save content (48%), share content (46%), receive notifications (44%), and be able to read offline (37%).

Respondents mobile applications preferences are that 54% would download a Statistics Canada mobile application; 63% would like to be notified of relevant news stories as they are published; 44% prefer mobile notifications over email notifications; and 40% prefer to download a mobile application on their mobile device to access news information, rather than navigate to a website.

Finally, 53% of respondents answered that they want to be notified if Statistics Canada publishes new data or articles throughout the day.

Report a problem or mistake on this page

Date modified:: 2023-01-09

Retail Commodity Survey: CVs for Total Sales (March 2021)

Retail Commodity Survey: CVs for Total Sales (March 2021)
NAPCS-CANADA	Month
NAPCS-CANADA	202012	202101	202102	202103
Total commodities, retail trade commissions and miscellaneous services	1.17	0.67	0.72	0.63
Retail Services (except commissions) [561]	1.15	0.67	0.72	0.63
Food at retail [56111]	0.90	0.98	0.99	0.65
Soft drinks and alcoholic beverages, at retail [56112]	0.59	0.68	0.63	0.53
Cannabis products, at retail [56113]	0.00	0.00	0.00	0.00
Clothing at retail [56121]	1.52	1.60	1.22	1.21
Footwear at retail [56122]	1.94	3.48	3.13	1.96
Jewellery and watches, luggage and briefcases, at retail [56123]	2.94	7.73	3.47	5.34
Home furniture, furnishings, housewares, appliances and electronics, at retail [56131]	0.70	0.94	0.97	0.76
Sporting and leisure products (except publications, audio and video recordings, and game software), at retail [56141]	1.67	2.68	2.87	2.27
Publications at retail [56142]	7.64	8.74	6.01	7.72
Audio and video recordings, and game software, at retail [56143]	6.88	3.16	7.15	5.54
Motor vehicles at retail [56151]	5.14	2.21	2.68	2.07
Recreational vehicles at retail [56152]	6.21	6.19	3.87	5.84
Motor vehicle parts, accessories and supplies, at retail [56153]	2.99	1.66	1.80	1.77
Automotive and household fuels, at retail [56161]	2.26	2.19	2.06	1.58
Home health products at retail [56171]	3.44	3.83	2.39	2.83
Infant care, personal and beauty products, at retail [56172]	3.14	2.33	2.32	2.29
Hardware, tools, renovation and lawn and garden products, at retail [56181]	1.69	1.77	2.11	1.79
Miscellaneous products at retail [56191]	2.12	2.57	2.44	3.24
Total retail trade commissions and miscellaneous services^{Footnote 1}	2.43	1.48	1.66	1.85
Footnotes Footnote 1 Comprises the following North American Product Classification System (NAPCS): 51411, 51412, 53112, 56211, 57111, 58111, 58121, 58122, 58131, 58141, 72332, 833111, 841, 85131 and 851511. Return to footnote 1 referrer

Why are we conducting this survey?

This survey collects information on scientific activities of Canadian businesses and industrial non-profit organizations. The research and development expenditures and personnel information is used by federal, provincial and territorial governments and agencies, academics, trade associations and international organizations for statistical analyses and policy purposes. These data also contribute to national totals of research and development activities. The payments and receipts information is used by these agencies to monitor knowledge flows across international borders and between Canadian organizations.

Your information may also be used by Statistics Canada for other statistical and research purposes.

Your participation in this survey is required under the authority of the Statistics Act.

Other important information

Authorization to collect this information

Data are collected under the authority of the Statistics Act, Revised Statutes of Canada, 1985, Chapter S-19.

Confidentiality

By law, Statistics Canada is prohibited from releasing any information it collects that could identify any person, business, or organization, unless consent has been given by the respondent, or as permitted by the Statistics Act. Statistics Canada will use the information from this survey for statistical purposes only.

Record linkages

To enhance the data from this survey and to reduce the reporting burden, Statistics Canada may combine the acquired data with information from other surveys or from administrative sources.

Data-sharing agreements

Provincial and territorial statistical agencies

Section 11 of the Statistics Act provides for the sharing of information with provincial and territorial statistical agencies that meet certain conditions. These agencies must have the legislative authority to collect the same information, on a mandatory basis, and the legislation must provide substantially the same provisions for confidentiality and penalties for disclosure of confidential information as the Statistics Act. Because these agencies have the legal authority to compel businesses to provide the same information, consent is not requested and businesses may not object to the sharing of the data.

For this survey, there are Section 11 agreements with the provincial and territorial statistical agencies of Newfoundland and Labrador, Nova Scotia, New Brunswick, Quebec, Ontario, Manitoba, Saskatchewan, Alberta, British Columbia and the Yukon. The shared data will be limited to information on in-house research and development expenditures (Question 15) and in-house research and development personnel (Question 73) pertaining to business establishments located within the jurisdiction of the respective province or territory.

Section 12 of the Statistics Act provides for the sharing of information with federal, provincial or territorial government organizations. Under Section 12, you may refuse to share your information with any of these organizations by writing a letter of objection to the Chief Statistician, specifying the organizations with which you do not want Statistics Canada to share your data and mailing it to the following address:

Chief Statistician of Canada
Statistics Canada
Attention of Director, Enterprise Statistics Division
150 Tunney's Pasture Driveway
Ottawa, Ontario
K1A 0T6

You may also contact us by email at statcan.esdhelpdesk-dsebureaudedepannage.statcan@statcan.gc.ca or by fax at 613-951-6583.

Other data-sharing agreement

For this survey, there are Section 12 agreements with the statistical agencies of Prince Edward Island, the Northwest Territories and Nunavut. The shared data will be limited to information on in-house research and development expenditures (Question 15) and in-house research and development personnel (Question 73) pertaining to business establishments located within the jurisdiction of the respective province or territory.

Innovation, Science and Economic Development Canada

For this survey, Statistics Canada will share survey data with Innovation, Science and Economic Development Canada. The shared data will be limited to information on research and development expenditures (Questions 5 to 22) and in-house research and development personnel (Questions 71 to 73).

Natural Resources Canada

For respondents with expenditures on energy-related research and development in technology (fossil fuels, renewable energy resources, nuclear fission and fusion, electric power, hydrogen and fuel cells, energy efficiency, other energy-related technologies), Statistics Canada will also share survey data with the Office of Energy Research and Development (OERD) of Natural Resources Canada. The shared data will be limited to information on Energy Research and Development Expenditures by Area of Technology (Questions 23 to 70).

Business or organization and contact information

1. Verify or provide the business or organization's legal and operating name and correct where needed.

Note: Legal name modifications should only be done to correct a spelling error or typo.

Legal Name

The legal name is one recognized by law, thus it is the name liable for pursuit or for debts incurred by the business or organization. In the case of a corporation, it is the legal name as fixed by its charter or the statute by which the corporation was created.

Modifications to the legal name should only be done to correct a spelling error or typo.

To indicate a legal name of another legal entity you should instead indicate it in question 3 by selecting 'Not currently operational' and then choosing the applicable reason and providing the legal name of this other entity along with any other requested information.

Operating Name

The operating name is a name the business or organization is commonly known as if different from its legal name. The operating name is synonymous with trade name.

Legal name
Operating name (if applicable)

2. Verify or provide the contact information of the designated business or organization contact person for this questionnaire and correct where needed.

Note: The designated contact person is the person who should receive this questionnaire. The designated contact person may not always be the one who actually completes the questionnaire.

First name
Last name
Title
Preferred language of communication
- English
- French
Mailing address (number and street)
City
Province, territory or state
Postal code or ZIP code
Country
- Canada
- United States
Email address
Telephone number (including area code)
Extension number (if applicable)
The maximum number of characters is 10.
Fax number (including area code)

3. Verify or provide the current operational status of the business or organization identified by the legal and operating name above.

Operational
Not currently operational
Why is this business or organization not currently operational?
- Seasonal operations
  - When did this business or organization close for the season?
    - Date
  - When does this business or organization expect to resume operations?
    - Date
- Ceased operations
  - When did this business or organization cease operations?
    - Date
  - Why did this business or organization cease operations?
    - Bankruptcy
    - Liquidation
    - Dissolution
    - Other - Specify the other reasons for ceased operations
- Sold operations
  - When was this business or organization sold?
    - Date
  - What is the legal name of the buyer?
- Amalgamated with other businesses or organizations
  - When did this business or organization amalgamate?
    - Date
  - What is the legal name of the resulting or continuing business or organization?
  - What are the legal names of the other amalgamated businesses or organizations?
- Temporarily inactive but will re-open
  - When did this business or organization become temporarily inactive?
    - Date
  - When does this business or organization expect to resume operations?
    - Date
  - Why is this business or organization temporarily inactive?
- No longer operating due to other reasons
  - When did this business or organization cease operations?
    - Date
  - Why did this business or organization cease operations?

4. Verify or provide the current main activity of the business or organization identified by the legal and operating name above.

Note: The described activity was assigned using the North American Industry Classification System (NAICS).

This question verifies the business or organization's current main activity as classified by the North American Industry Classification System (NAICS). The North American Industry Classification System (NAICS) is an industry classification system developed by the statistical agencies of Canada, Mexico and the United States. Created against the background of the North American Free Trade Agreement, it is designed to provide common definitions of the industrial structure of the three countries and a common statistical framework to facilitate the analysis of the three economies. NAICS is based on supply-side or production-oriented principles, to ensure that industrial data, classified to NAICS, are suitable for the analysis of production-related issues such as industrial performance.

The target entity for which NAICS is designed are businesses and other organizations engaged in the production of goods and services. They include farms, incorporated and unincorporated businesses and government business enterprises. They also include government institutions and agencies engaged in the production of marketed and non-marketed services, as well as organizations such as professional associations and unions and charitable or non-profit organizations and the employees of households.

The associated NAICS should reflect those activities conducted by the business or organizational units targeted by this questionnaire only, as identified in the 'Answering this questionnaire' section and which can be identified by the specified legal and operating name. The main activity is the activity which most defines the targeted business or organization's main purpose or reason for existence. For a business or organization that is for-profit, it is normally the activity that generates the majority of the revenue for the entity.

The NAICS classification contains a limited number of activity classifications; the associated classification might be applicable for this business or organization even if it is not exactly how you would describe this business or organization's main activity.

Please note that any modifications to the main activity through your response to this question might not necessarily be reflected prior to the transmitting of subsequent questionnaires and as a result they may not contain this updated information.

The following is the detailed description including any applicable examples or exclusions for the classification currently associated with this business or organization.

Description and examples

This is the current main activity
- Provide a brief but precise description of this business or organization's main activity
  e.g., breakfast cereal manufacturing, shoe store, software development
This is not the current main activity

Main activity

5. You indicated that is not the current main activity.

Was this business or organization's main activity ever classified as:?

Yes
- When did the main activity change?
  Date
No

6. Search and select the industry classification code that best corresponds to this business or organization's main activity.

How to search:

if desired, you can filter the search results by first selecting this business or organization's activity sector
enter keywords or a brief description that best describes this business or organization main activity
press the Search button to search the database for an activity that best matches the keywords or description you provided
then select an activity from the list.

Select this business or organization's activity sector (optional)

Farming or logging operation
Construction company or general contractor
Manufacturer
Wholesaler
Retailer
Provider of passenger or freight transportation
Provider of investment, savings or insurance products
Real estate agency, real estate brokerage or leasing company
Provider of professional, scientific or technical services
Provider of health care or social services
Restaurant, bar, hotel, motel or other lodging establishment
Other sector

Enter keywords or a brief description, then press the Search button

Additional reporting instructions

1. Throughout this questionnaire, please report financial information in thousands of Canadian dollars.

For example, an amount of $763,880.25 should be reported as: CAN$ 764,000

I will report in the format above

Organization status

Reporting period

1. What is the end date of this organization's fiscal year?

Note: For this survey, this organization's fiscal year end date should fall on or before March 31, 2021.

Here are some examples of fiscal periods that fall within the targeted dates:

May 1, 2019 to April 30, 2020
July 1, 2019 to June 30, 2020
October 1, 2019 to September 30, 2020
January 1, 2020 to December 31, 2020
February 1, 2020 to January 31, 2021
April 1, 2020 to March 31, 2021

Fiscal Year-End date

This fiscal year will be referred to as 2020 throughout the questionnaire

Organization status

2. What is this organization's GST number (9-digit business number)?

GST number (9-digit business number)

3. In 2020, what were this organization's total expenditures within Canada?

Please report all amounts in thousands of Canadian dollars.

If precise figures are not available, please provide your best estimate.

Total expenditures represent the total budget for all operations of this organization in the fiscal period. If 'total expenditures' cannot be calculated, total funds (from members, government programs and all other sources of funds) or total revenues may be provided.

CAN$ '000

In-house research and development ( R&D ) expenditures

Before you begin, for this survey

'In-house R&D ' refers to

Expenditures within Canada for R&D performed within this organization by:

employees (permanent, temporary or casual)
self-employed individuals or contractors who are working on-site on this organization's R&D projects.

'Outsourced R&D ' refers to

Payments made within or outside Canada to other organizations, businesses or individuals to fund R&D performance:

grants
fellowships
contracts.

4. In 2020, did this organization have expenditures for R&D performed in-house within Canada?

Exclude payments for outsourced (contracted out or granted) R&D, which should be reported in question 10.

In-house refers to R&D which is performed on-site or within the organization's establishment. Exclude R&D expenses performed by other companies or organizations. A later question will collect these data.

Research and experimental development ( R&D ) comprise creative and systematic work undertaken in order to increase the stock of knowledge - including knowledge of humankind, culture and society - and to devise new applications of available knowledge.

R&D is performed in the natural sciences, engineering, social sciences and humanities. There are three types of R&D activities: basic research, applied research and experimental development.

Research work in the social sciences

Include if projects are employing new or significantly different modelling techniques or developing new formulae, analyzing data not previously available or applying new research techniques, development of community strategies for disease prevention, or health education.

Exclude:

routine analytical projects using standard techniques and existing data
routine market research
routine statistical analysis intended for on-going monitoring of an activity.

5. In 2020, what were this organization's expenditures for R&D performed in-house within Canada?

Exclude payments for outsourced (contracted out or granted) R&D, which should be reported in question 10.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In-house R&D expenditures are composed of current in-house R&D expenditures and capital in-house R&D expenditures.

Current in-house R&D expenditures

Include:

wages, salaries, benefits and fringe benefits, materials and supplies
services to support R&D, including on-site R&D consultants and contractors
necessary background literature
minor scientific equipment
associated administrative overhead costs.

a. Wages, salaries of permanent, temporary and casual R&D employees

Include benefits and fringe benefits of employees engaged in R&D activities. Benefits and fringe benefits include bonus payments, holiday or vacation pay, pension fund contributions, other social security payments, payroll taxes, etc.

b. Services to support R&D

Include:

payments to on-site R&D consultants and contractors working under the direct control of your business
other services including indirect services purchased to support in-house R&D such as security, storage, repair, maintenance and use of buildings and equipment
computer services, software licensing fees and dissemination of R&D findings.

c. R&D materials

Include:

water, fuel, gas and electricity
materials for creation of prototypes
reference materials (books, journals, etc.)
subscriptions to libraries and data bases, memberships to scientific societies, etc.
cost of outsourced (contracted out or granted) small R&D prototypes or R&D models
materials for laboratories (chemicals, animal, etc.)
all other R&D -related materials.

d. All other current R&D costs including overhead

Include administrative and overhead costs (e.g., office, lease/rent, post and telecommunications, internet, legal expenditures, insurance), prorated if necessary to allow for non- R&D activities within the business.

Exclude:

interest charges
value-added taxes (goods and services tax (GST) or harmonized sales tax (HST)).

Capital in-house expenditures are the annual gross amount paid for the acquisition of fixed assets that are used repeatedly, or continuously in the performance of R&D for more than one year. Report capital in-house expenditures in full for the period when they occurred.

Include costs for software, land, buildings and structures, equipment, machinery and other capital costs.

Exclude capital depreciation.

e. Software

Include applications and systems software (original, customized and off-the-shelf software), supporting documentation and other software-related acquisitions.

f. Land acquired for R&D including testing grounds, sites for laboratories and pilot plants.

g. Buildings and structures that are constructed or purchased for R&D activities or that have undergone major improvements, modifications, renovations and repairs for R&D activities.

h. Equipment, machinery and all other capital

Include major equipment, machinery and instruments, including embedded software, acquired for R&D activities.

In 2020, what were this organization's expenditures for R&D performed in-house within Canada?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
2020 - Current in-house R&D expenditures within Canada
Wages, salaries of permanent, temporary and casual R&D employees
Services to support R&D
R&D materials
All other current R&D costs
2020 — Total current in-house R&D expenditures within Canada
2020 — Capital in-house R&D expenditures within Canada
Software
Land
Buildings and structures
Equipment, machinery and all other capital
2020 — Total capital in-house R&D expenditures within Canada
2020 — Total in-house R&D expenditures within Canada

6. In 2021 and 2022, does this organization plan to have expenditures for R&D performed in-house within Canada?

Exclude payments for outsourced (contracted out or granted) R&D, which should be reported in question 12.

Select all that apply.

In-house R&D expenditures are composed of current in-house R&D expenditures and capital in-house R&D expenditures.

Inclusions

Prototypes
Include design, construction and operation of prototypes, provided that the primary objective is to make further improvements or to undertake technical testing.
Exclude if the prototype is for commercial purposes.

Clinical Trials
Include clinical trial phases 1, 2, and 3. Include clinical trial phase 4 only if it brings about a further scientific or technological advance.

Pilot plants
Include construction and operation of pilot plants, provided that the primary objective is to make further improvements or to undertake technical testing.
Exclude if the pilot plant is intended to be operated for commercial purposes.

New computer software or significant improvements/modifications to existing computer software
Includes technological or scientific advances in theoretical computer sciences; operating systems e.g., improvement in interface management, developing new operating system of converting an existing operating system to a significantly different hardware environment; programming languages; and applications if a significant technological change occurs.

Contracts
Include all contracts which require R&D. For contracts which include other work, report only the R&D costs.

Research work in the social sciences
Include if projects are employing new or significantly different modelling techniques or developing new formulae, analyzing data not previously available or applying new research techniques, development of community strategies for disease prevention, analysis of the effectiveness of health interventions, or health education.

Exclusions

Routine analysis in the social sciences including policy-related studies, management studies and efficiency studies
Exclude analytical projects of a routine nature, with established methodologies, principles and models of the related social sciences to bear on a particular problem (e.g., commentary on the probable economic effects of a change in the tax structure, using existing economic data; use of standard techniques in applied psychology to select and classify industrial and military personnel, students, etc., and to test children with reading or other disabilities).

Consumer surveys, advertising, market research
Exclude projects of a routine nature, with established methodologies intended for commercialization of the results of R&D.

Routine quality control and testing
Exclude projects of a routine nature, with established methodologies not intended to create new knowledge, even if carried out by personnel normally engaged in R&D.

Pre-production activities such as demonstration of commercial viability, tooling up, trial production, trouble shooting
Although R&D may be required as a result of these steps, these activities are excluded.

Prospecting, exploratory drilling, development of mines, oil or gas wells
Include only if for R&D projects concerned with new equipment or techniques in these activities, such as in-situ and tertiary recovery research.

Engineering
Exclude engineering unless it is in direct support of R&D.

Design and drawing
Exclude design and drawing unless it is in direct support of R&D.

Patent and licence work
Exclude all administrative and legal work connected with patents and licences.

Cosmetic modifications or style changes to existing products
Exclude if no significant technical improvement or modification to the existing products has occurred.

General purpose or routine data collection
Exclude projects of a routine nature, with established methodologies intended for on-going monitoring of an activity.

Routine computer programming, systems maintenance or software application
Exclude projects of a routine nature, with established methodologies intended to support on-going operations.

Routine mathematical or statistical analysis or operations analysis
Exclude projects of a routine nature, with established methodologies intended for on-going monitoring of an activity.

Activities associated with standards compliance
Exclude projects of a routine nature, with established methodologies intended to support standards compliance.

Specialized routine medical care such as routine pathology services
Exclude projects of a routine nature, with established methodologies intended for on-going monitoring of an activity where results do not further scientific, technological advance, or understanding of the effectiveness of a technology.

In 2021
In 2022
No planned in-house R&D expenditures

7. In 2021, what are this organization's planned expenditures for R&D performed in-house within Canada?

Exclude payments for outsourced (contracted out or granted) R&D, which should be reported in question 12.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2021, what are this organization's planned expenditures for R&D performed in-house within Canada?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
2021 — Total current in-house R&D expenditures within Canada
2021 — Total capital in-house R&D expenditures within Canada

8. In 2022, what are this organization's planned expenditures for R&D performed in-house within Canada?

Exclude payments for outsourced (contracted out or granted) R&D, which should be reported in question 12.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2022, what are this organization's planned expenditures for R&D performed in-house within Canada?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
2022 — Total current in-house R&D expenditures within Canada
2022 — Total capital in-house R&D expenditures within Canada

Outsourced (contracted out or granted) R&D expenditures

9. In 2020, did this organization have outsourced (contracted out or granted) R&D expenditures within Canada or outside Canada?

Include:

funding or grants provided to other organizations to perform R&D
contracted out expenditures for R&D.

Exclude services of self-employed individuals or contractors who are working on-site on this organization's R&D projects, which should be reported in question 5.

Outsourced (contracted out or granted) R&D expenditures are payments made through contracts, grants and fellowships to another company, organization or individual to purchase R&D activities.

Within Canada
Outside Canada
No payment made to others to perform R&D

10. In 2020, what were this organization's outsourced (contracted out or granted) R&D expenditures within Canada or outside Canada?

Include:

funding or grants provided to other organizations to perform R&D
contracted out expenditures for R&D.

Exclude services of self-employed individuals or contractors who are working on-site on this organization's R&D projects, which should be reported in question 5.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Include payments made through contracts, grants, donations and fellowships to another company, organization or individual to purchase or fund R&D activities.

Exclude expenditures for on-site R&D contractors.

Companies include all incorporated for-profit businesses and government business enterprises providing products in the market at market rates.

Private non-profit organizations include voluntary health organizations, private philanthropic foundations, associations, consortia, accelerators, and societies and research institutes. They are not-for-profit organizations that serve the public interest by supporting activities related to public welfare (such as health, education, the environment).

Industrial research institutes or associations include all non-profit organizations that serve the business sector, with industrial associations frequently consisting of their membership.

Universities include hospitals and clinics when they are affiliated with a university and provide education services or when R&D activity is under the direct control of a university.

Federal government includes all federal government departments and agencies. It excludes federal government business enterprises providing products in the market.

Provincial or territorial governments include all provincial or territorial government ministries, departments and agencies. It excludes provincial or territorial government business enterprises providing products in the market.

Provincial or territorial research organizations are organizations created under provincial or territorial law which conduct or facilitate research on behalf of the province or territory.

Other organizations - individuals, non-university educational institutions, for profit accelerators and incubators, foreign governments including ministries, departments and agencies of foreign governments.

In 2020, what were this organization's outsourced (contracted out or granted) R&D expenditures within Canada or outside Canada?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	Within Canada CAN$ '000	Outside Canada CAN$ '000
Companies
Private non-profit organizations
Industrial research institutes or associations
Hospitals
Universities
Federal government departments and agencies
Provincial or territorial government departments, ministries and agencies
Provincial or territorial research organizations
Other organizations
2020 — Total outsourced (contracted out or granted) R&D expenditures

11. In 2021 and 2022, does this organization plan to outsource (contract out or grant) R&D expenditures within Canada or outside Canada?

Include:

funding or grants provided to other organizations to perform R&D
contracted out expenditures for R&D.

Exclude services of self-employed individuals or contractors who are working on-site on this organization's R&D projects, which should be reported in questions 7 and 8.

Select all that apply.

Outsourced (contracted out or granted) R&D expenditures are payments made through contracts, grants and fellowships to another company, organization or individual to purchase R&D activities.

In 2021
In 2022
No planned payments to others to perform R&D

12. In 2021 and 2022, what are this organization's planned outsourced (contracted out or granted) R&D expenditures within Canada or outside Canada?

Include:

funding or grants provided to other organizations to perform R&D
contracted out expenditures for R&D.

Exclude services of self-employed individuals or contractors who are working on-site on this organization's R&D projects, which should be reported in questions 7 and 8.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Include payments made through contracts, licenses, grants, donations, endowments and fellowships to another company, university, hospital, consortia, organization or individual to purchase or fund R&D activities.

Exclude expenditures for on-site R&D contractors.

In 2021 and 2022, what are this organization's planned outsourced (contracted out or granted) R&D expenditures within Canada or outside Canada?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	Within Canada CAN$ '000	Outside Canada CAN$ '000
2021
2022

In-house and Outsourced (contracted out or granted) R&D expenditures from 2020 to 2022

13. Summary of total R&D expenditures from 2020 to 2022
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	2020 CAN$ '000	2021 CAN$ '000	2022 CAN$ '000
Total current in-house R&D expenditures within Canada
Total capital in-house R&D expenditures within Canada
Total in-house R&D expenditures within Canada
Total outsourced (contracted out or granted) R&D expenditures
Total R&D expenditures

Geographic distribution of in-house R&D expenditures within Canada in 2020

14. In 2020, in which provinces or territories did this organization have expenditures for R&D performed in-house?

Exclude:

payments for outsourced (contracted out or granted) R&D, which should be reported in question 10
capital depreciation.

Select all that apply.

Newfoundland and Labrador
Prince Edward Island
Nova Scotia
New Brunswick
Quebec
Ontario
Manitoba
Saskatchewan
Alberta
British Columbia
Yukon
Northwest Territories
Nunavut

15. In 2020, how were this organization's total expenditures for R&D performed in-house distributed by province or territory?

Exclude:

payments for outsourced (contracted out or granted) R&D, which should be reported in question 10
capital depreciation.

Please report all amounts in thousands of Canadian dollars.

For in-house R&D activities on federal lands, please include in the closest province or territory.

In 2020, how were this organization's total expenditures for R&D performed in-house distributed by province or territory?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	Current in-house R&D expenditures CAN$ '000	Capital in-house R&D expenditures CAN$ '000
Newfoundland and Labrador
Prince Edward Island
Nova Scotia
New Brunswick
Quebec
Ontario
Manitoba
Saskatchewan
Alberta
British Columbia
Yukon
Northwest Territories
Nunavut
2020 — Total current and capital in-house R&D expenditures
2020 — Total current and capital in-house R&D expenditures previously reported from question 5

Sources of funds for in-house R&D expenditures in 2020

16. In 2020, what were the sources of funds for this organization's total expenditures for R&D performed in-house?

Include Canadian and foreign sources.

Exclude:

payments for outsourced (contracted out or granted) R&D, which should be reported in question 10
capital depreciation.

Select all that apply.

Funds from this organization
Amount contributed by this organization to R&D performed within Canada (include interest payments and other income, land, buildings, machinery and equipment (capital expenditures) purchased for R&D ).

Funds from member companies or affiliates
Amount received from member organizations and affiliated organizations used to perform R&D within Canada (include annual fees and sustaining grants, land, buildings, machinery and equipment (capital expenditures) purchased for R&D ).

R&D contract work for companies
Funds received from companies to perform R&D on their behalf.

Federal government grants or funding
Grants or funds received from the federal government in support of R&D activities not connected to a specific contractual deliverable.

Federal government contracts
Funds received from the federal government in support of R&D activities connected to a specific contractual deliverable.

Provincial or territorial government grants or funding
Grants or funds received from the provincial or territorial government in support of R&D activities not connected to a specific contractual deliverable.

Provincial or territorial government contracts
Funds received from the provincial or territorial government in support of R&D activities connected to a specific contractual deliverable.

R&D contract work for private non-profit organizations
Funds received from non-profit organizations to perform R&D on their behalf.

Other sources
Funds received from all other sources not previously classified.

Funds from this organization
Include interest payments and other income.
Funds from member companies or affiliates
Include annual fees and sustaining grants.
Federal government grants or funding
Include R&D grants or funding or R&D portion only of other grants or funding.
Federal government contracts
Include R&D contracts or R&D portion only of other contracts.
R&D contract work for companies
Provincial or territorial government grants or funding
Include R&D grants or funding or R&D portion only of other grants or funding.
From which province or territory did this organization receive provincial or territorial government R&D grants or funding? Select all that apply.
- Newfoundland and Labrador
- Prince Edward Island
- Nova Scotia
- New Brunswick
- Quebec
- Ontario
- Manitoba
- Saskatchewan
- Alberta
- British Columbia
- Yukon
- Northwest Territories
- Nunavut
Provincial or territorial government contracts
Include R&D contracts or R&D portion only of other contracts.
From which province or territory did this organization receive provincial or territorial government R&D contracts? Select all that apply.
- Newfoundland and Labrador
- Prince Edward Island
- Nova Scotia
- New Brunswick
- Quebec
- Ontario
- Manitoba
- Saskatchewan
- Alberta
- British Columbia
- Yukon
- Northwest Territories
- Nunavut
R&D contract work for private non-profit organizations
Other sources
e.g., universities, foreign governments, individuals

17. In 2020, what were the sources of funds for this organization's total expenditures of $ [Amount] for R&D performed in-house?

Exclude:

payments for outsourced (contracted out or granted) R&D, which should be reported in question 10
capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

R&D contract work for companies
Funds received from companies to perform R&D on their behalf.

Federal government grants or funding
Grants or funds received from the federal government in support of R&D activities not connected to a specific contractual deliverable.

Federal government contracts
Funds received from the federal government in support of R&D activities connected to a specific contractual deliverable.

Provincial or territorial government contracts
Funds received from the provincial or territorial government in support of R&D activities connected to a specific contractual deliverable.

R&D contract work for private non-profit organizations
Funds received from non-profit organizations to perform R&D on their behalf.

Other sources
Funds received from all other sources not previously classified.

In 2020, what were the sources of funds for this organization's total expenditures of $ [Amount] for R&D performed in-house?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	From within Canada CAN$ '000	From outside Canada CAN$ '000
Funds from this organization
Funds from member companies or affiliates
Federal government grants or funding
Federal government contracts
R&D contract work for companies
Business 1
Business 2
Business 3
Business 4
Other contracts not listed above
Provincial or territorial government grants or funding
Newfoundland and Labrador
Prince Edward Island
Nova Scotia
New Brunswick
Quebec
Ontario
Manitoba
Saskatchewan
Alberta
British Columbia
Yukon
Northwest Territories
Nunavut
Provincial or territorial government contracts
Newfoundland and Labrador
Prince Edward Island
Nova Scotia
New Brunswick
Quebec
Ontario
Manitoba
Saskatchewan
Alberta
British Columbia
Yukon
Northwest Territories
Nunavut
R&D contract work for private non-profit organizations
Organization 1
Organization 2
Organization 3
Other sources
Other sources
2020 — Total in-house R&D expenditures by sources of funds by origin
2020 — Total in-house R&D expenditures (Canadian and foreign sources)
Total in-house R&D expenditures previously reported from question 5

Fields of R&D for in-house R&D expenditures within Canada in 2020

18. In 2020, in which field(s) of research and development did this organization have R&D performed in-house within Canada?

Exclude:

payments for outsourced (contracted out or granted) R&D, which should be reported in question 10
capital depreciation.

Select all that apply.

Natural and formal sciences: physical sciences, chemical sciences, earth and related environmental sciences, biological sciences, other natural sciences.

Engineering and technology: civil engineering, electrical engineering, electronic engineering and communications technology, mechanical engineering, chemical engineering, materials engineering, medical engineering, environmental engineering, environmental biotechnology, industrial biotechnology, nanotechnology, other engineering and technologies.

Software-related sciences and technology: software engineering and technology, computer sciences, information technology and bioinformatics.

Medical and health sciences: basic medicine, clinical medicine, health sciences, medical biotechnology, other medical sciences.

Agricultural sciences: agriculture, forestry and fisheries sciences, animal and dairy sciences, veterinary sciences, agricultural biotechnology, other agricultural sciences.

Social sciences and humanities: psychology, educational sciences, economics and business, other social sciences, humanities.

Natural and formal sciences
Exclude computer sciences, information sciences and bioinformatics.
Engineering and technology
Exclude software engineering and technology.
Software-related sciences and technology
Medical and health sciences
Agricultural sciences
Social sciences and humanities

19. In 2020, how were this organization's total expenditures of $ [Amount] for R&D performed in-house within Canada distributed by field(s) of research and development?

Exclude:

payments for outsourced (contracted out or granted) R&D, which should be reported in question 10
capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Natural and formal sciences

Mathematics: pure mathematics, applied mathematics, statistics and probability.

Physical sciences: atomic, molecular and chemical physics, interaction with radiation, magnetic resonances, condensed matter physics, solid state physics and superconductivity, particles and fields physics, nuclear physics, fluids and plasma physics (including surface physics), optics (including laser optics and quantum optics), acoustics, astronomy (including astrophysics, space science).

Chemical sciences: organic chemistry, inorganic and nuclear chemistry, physical chemistry, polymer science and plastics, electrochemistry (dry cells, batteries, fuel cells, metal corrosion, electrolysis), colloid chemistry, analytical chemistry.

Earth and related environmental sciences: geosciences, geophysics, mineralogy and palaeontology, geochemistry and geophysics, physical geography, geology and volcanology, environmental sciences, meteorology, atmospheric sciences and climatic research, oceanography, hydrology and water resources.

Biological sciences: cell biology, microbiology and virology, biochemistry, molecular biology and biochemical research, mycology, biophysics, genetics and heredity (medical genetics under medical biotechnology), reproductive biology (medical aspects under medical biotechnology), developmental biology, plant sciences and botany, zoology, ornithology, entomology and behavioural sciences biology, marine biology, freshwater biology and limnology, ecology and biodiversity conservation, biology (theoretical, thermal, cryobiology, biological rhythm), evolutionary biology.

Other natural sciences: other natural sciences.

Engineering and technology

Civil engineering: civil engineering, architecture engineering, municipal and structural engineering, transport engineering.

Electrical engineering, electronic engineering and communications technology: electrical and electronic engineering, robotics and automatic control, micro-electronics, semiconductors, automation and control systems, communication engineering and systems, telecommunications, computer hardware and architecture.

Mechanical engineering: mechanical engineering, applied mechanics, thermodynamics, aerospace engineering, nuclear-related engineering (nuclear physics under Physical sciences), acoustical engineering, reliability analysis and non-destructive testing, automotive and transportation engineering and manufacturing, tooling, machinery and equipment engineering and manufacturing, heating, ventilation and air conditioning engineering and manufacturing.

Chemical engineering: chemical engineering (plants, products), chemical process engineering.

Materials engineering: materials engineering and metallurgy, ceramics, coating and films (including packaging and printing), plastics, rubber and composites (including laminates and reinforced plastics), paper and wood and textiles, construction materials (organic and inorganic).

Medical engineering: medical and biomedical engineering, medical laboratory technology (excluding biomaterials which should be reported under Industrial biotechnology).

Environmental engineering: environmental and geological engineering, petroleum engineering (fuel, oils), energy and fuels, remote sensing, mining and mineral processing, marine engineering, sea vessels and ocean engineering.

Environmental biotechnology: environmental biotechnology, bioremediation, diagnostic biotechnologies in environmental management (DNA chips and bio-sensing devices).

Industrial biotechnology: industrial biotechnology, bioprocessing technologies, biocatalysis and fermentation bioproducts (products that are manufactured using biological material as feedstock), biomaterials (bioplastics, biofuels, bio-derived bulk and fine chemicals, bio-derived materials).

Nanotechnology: nano-materials (production and properties), nano-processes (applications on nano-scale).

Other engineering and technologies: food and beverages, oenology, other engineering and technologies.

Software-related sciences and technologies

Software engineering and technology: computer software engineering, computer software technology, and other related computer software engineering and technologies.

Computer sciences: computer science, artificial intelligence, cryptography, and other related computer sciences.

Information technology and bioinformatics: information technology, informatics, bioinformatics, biomathematics, and other related information technologies.

Medical and health sciences

Basic medicine: anatomy and morphology (plant science under Biological science), human genetics, immunology, neurosciences, pharmacology and pharmacy and medicinal chemistry, toxicology, physiology and cytology, pathology.

Clinical medicine: andrology, obstetrics and gynaecology, paediatrics, cardiac and cardiovascular systems, haematology, anaesthesiology, orthopaedics, radiology and nuclear medicine, dentistry, oral surgery and medicine, dermatology, venereal diseases and allergy, rheumatology, endocrinology and metabolism and gastroenterology, urology and nephrology, and oncology.

Health sciences: health care sciences and nursing, nutrition and dietetics, parasitology, infectious diseases and epidemiology, occupational health.

Medical biotechnology: health-related biotechnology, technologies involving the manipulation of cells, tissues, organs or the whole organism, technologies involving identifying the functioning of DNA, proteins and enzymes, pharmacogenomics, gene-based therapeutics, biomaterials (related to medical implants, devices, sensors).

Other medical sciences: forensic science, other medical sciences.

Agricultural sciences

Agriculture, forestry and fisheries sciences: agriculture, forestry, fisheries and aquaculture, soil science, horticulture, viticulture, agronomy, plant breeding and plant protection.

Animal and dairy sciences: animal and dairy science, animal husbandry.

Veterinary sciences: veterinary science (all).

Agricultural biotechnology: agricultural biotechnology and food biotechnology, genetically modified (GM) organism technology and livestock cloning, diagnostics (DNA chips and biosensing devices), biomass feedstock production technologies and biopharming.

Other agricultural sciences: other agricultural sciences.

Social sciences and humanities

Psychology: cognitive psychology and psycholinguistics, experimental psychology, psychometrics and quantitative psychology, and other fields of psychology.

Educational sciences: education, training and other related educational sciences.

Economics and business: micro-economics, macro-economics, econometrics, labour economics, financial economics, business economics, entrepreneurial and business administration, management and operations, management sciences, finance, pharmacoeconomics, and all other related fields of economics and business.

Other social sciences: anthropology (social and cultural) and ethnology, demography, geography (human, economic and social), planning (town, city and country), management, organisation and methods (excluding market research unless new methods/techniques are developed), law, linguistics, political sciences, sociology, miscellaneous social sciences and interdisciplinary, and methodological and historical science and technology activities relating to subjects in this group.

Humanities: history (history, prehistory and history, together with auxiliary historical disciplines such as archaeology, numismatics, palaeography, genealogy, etc.), languages and literature (ancient and modern), other humanities (philosophy (including the history of science and technology)), arts (history of art, art criticism, painting, sculpture, musicology, dramatic art excluding artistic "research" of any kind), religion, theology, other fields and subjects pertaining to the humanities, and methodological, historical and other science and technology activities relating to the subjects in this group.

In 2020, how were this organization's total expenditures of $ [Amount] for R&D performed in-house within Canada distributed by field(s) of research and development?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Natural and formal sciences
Mathematics
Physical sciences
Chemical sciences
Earth and related environmental sciences
Biological sciences
Other natural sciences
Total natural and formal sciences
Engineering and technology
Civil engineering
Electrical engineering, electronic engineering and communications technology
Mechanical engineering
Chemical engineering
Materials engineering
Medical engineering
Environmental engineering
Environmental biotechnology
Industrial biotechnology
Nanotechnology
Other engineering and technologies
Total engineering and technology
Software-related sciences and technology
Software engineering and technology
Computer sciences
Information technology and bioinformatics
Total software-related sciences and technology
Medical and health sciences
Basic medicine
Clinical medicine
Health sciences
Medical biotechnology
Other medical sciences
Total medical and health sciences
Agricultural sciences
Agriculture, forestry and fisheries sciences
Animal and dairy sciences
Veterinary sciences
Agricultural biotechnology
Other agricultural sciences
Total agricultural sciences
Social sciences and humanities
Psychology
Educational sciences
Economics and business
Other social sciences
Humanities
Total social sciences and humanities
2020 — Total in-house R&D expenditures within Canada by field of research and development
Total in-house R&D expenditures previously reported from question 5

20. Summary of 2020 total in-house R&D expenditures within Canada distributed by field(s) of research and development
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Total natural and formal sciences
Total engineering and technology
Total software-related sciences and technologies
Total medical and health sciences
Total agricultural sciences
Total social sciences and humanities
Total in-house R&D expenditures within Canada by fields of research and development

Nature of R&D for in-house R&D expenditures within Canada in 2020

21. In 2020, how were this organization's total expenditures of $ [Amount] for R&D performed in-house within Canada distributed by nature of R&D?

Basic research is experimental or theoretical work undertaken primarily to acquire new knowledge of the underlying foundation of phenomena and observable facts, without any particular application or use in view.

Applied research is original investigation undertaken in order to acquire new knowledge. It is, however, directed primarily towards a specific, practical aim or objective.

Experimental development is systematic work, drawing on knowledge gained from research and practical experience and producing additional knowledge, which is directed to producing new products or processes or to improving existing products or processes.

(OECD. Frascati Manual: Proposed Standard for Surveys on Research and Experimental Development, 2015)

In 2020, how were this organization's total expenditures of $ [Amount] for R&D performed in-house within Canada distributed by nature of R&D?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	Percentage of total in-house R&D expenditures
Basic research
Applied research
Experimental development
Total percentage

Results of R&D expenditures from 2018 to 2020

22. During the three (3) years 2018, 2019 and 2020, did this organization's total expenditures for R&D performed in-house and outsourced (contracted out or granted) within Canada or outside Canada lead to new or significant improvements to the following?

Goods

Goods developed through new knowledge from research discoveries include determination of effectiveness of existing treatment protocols, establishment of new treatment protocols (including diagnostic procedures, tests and protocols), and creation of new service delivery models and reference tools (including electronic applications).

During the three (3) years 2018, 2019 and 2020, did this organization's total expenditures for R&D performed in-house and outsourced (contracted out or granted) within Canada or outside Canada lead to new or significant improvements to the following?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	Yes	No
Goods
Services
Methods of manufacturing or producing goods and services
Logistics, delivery or distribution methods for this organization's inputs, goods or services
Supporting activities for this organization's processes, such as maintenance systems or operations for purchasing, accounting or computing

Energy-related R&D by area of technology

23. In 2020, did this organization's total in-house and outsourced (contracted out or granted) R&D expenditures include energy-related R&D in the following categories?

Fossil fuels: crude oils and natural gas exploration, crude oils and natural gas production, oil sands and heavy crude oils surface and sub-surface production and separation of the bitumen, tailings management, refining, processing and upgrading, coal production, separation and processing, transportation of fossil fuels.
Renewable energy resources: solar photovoltaics (PV), solar thermal-power and high-temperature applications, solar heating and cooling, wind energy, bio-energy - biomass production, bio-energy - biomass conversion to fuels, bio-energy - biomass conversion to heat and electricity, and other bio-energy, small hydro (less than 10 MW), large hydro (greater than or equal to 10 MW), other renewable energy.
Nuclear: materials exploration, mining and preparation, tailings management, nuclear reactors, other fission, fusion.
Electric power: generation in utility sector, combined heat and power in industry and in buildings, electricity transmission, distribution and storage of electricity.
Hydrogen and fuel cells: hydrogen production for process applications, hydrogen production for transportation applications, hydrogen transport and storage, other hydrogen, fuel cells, both stationary and mobile.
Energy efficiency: industry, residential and commercial, transportation, other energy efficiency.
Other energy-related technologies: carbon capture, transportation and storage for fossil fuel production and processing, electric power generation, industry in end-use sector, energy systems analysis, all other energy-related technologies.

In 2020, did this organization's total in-house and outsourced (contracted out or granted) R&D expenditures include energy-related R&D in the following categories?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	Yes	No
Fossil fuels
Renewable energy resources
Nuclear fission and fusion
Electric power
Hydrogen and fuel cells
Energy efficiency
Other energy-related technologies

Energy-related R&D by area of technology - Fossil fuels

24. In 2020, did this organization's total in-house and outsourced (contracted out or granted) R&D expenditures include fossil fuels-related R&D in the following categories?

Select all that apply.

Crude oils and natural gas exploration:
Include development of advanced exploration methods (geophysical, geochemical, seismic, magnetic) for on-shore and off-shore prospecting.

Crude oil and natural gas production (including enhanced recovery) and storage:
Include on-shore and off-shore deep drilling equipment and techniques for conventional oil and gas, secondary and tertiary recovery of oil and gas, hydro fracturing techniques, processing and cleaning of raw product, storage on remote platforms (e.g., Arctic, off-shore), safety aspects of off-shore platforms.

Oil sands and heavy crude oils surface and sub-surface production and separation of the bitumen, tailings management:
Include surface and in-situ production (e.g., SAGD), tailings management.

Refining, processing and upgrading:
Include processing of natural gas to pipeline specifications, and refining of conventional crude oils to refined petroleum products (RPPs), and the upgrading of bitumen and heavy oils either to synthetic crude oil or to RPPs. Upgrading may be done at an oil sands plant, regional merchant upgraders or integrated into a refinery producing RPPs.

Coal production, separation and processing:
Include coal, lignite and peat exploration, deposit evaluation techniques, mining techniques, separation techniques, coking and blending, other processing such as coal to liquids, underground (in-situ) gasification.

Transportation of fossil fuels:
Include transport of gaseous, liquid and solid hydrocarbons via pipelines (land and submarine) and their network evaluation, safety aspects of LNG transport and storage.

Crude oils and natural gas exploration
Crude oils and natural gas production and storage
Include enhanced recovery natural gas production.
Oil sands and heavy crude oil surface and sub-surface production and separation of bitumen, tailings management
Refining, processing and upgrading of fossil fuels
Coal production, separation and processing
Transportation of fossil fuels
None of the above

Energy-related R&D by area of technology

Report all 2020 R&D expenditures for fossil fuels within this reporting unit.

25. In 2020, what were this organization's energy R&D expenditures on crude oils and natural gas exploration?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Crude oils and natural gas exploration:
Include development of advanced exploration methods (geophysical, geochemical, seismic, magnetic) for on-shore and off-shore prospecting.

CAPTION
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for fossil fuels within this reporting unit.

26. In 2020, what were this organization's energy R&D expenditures on crude oils and natural gas production and storage?

Include enhanced recovery.

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2020, what were this organization's energy R&D expenditures on crude oils and natural gas production and storage?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for fossil fuels within this reporting unit.

27. In 2020, what were this organization's energy R&D expenditures on oil sands and heavy crude oil surface and sub-surface production and separation of bitumen, tailings management?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Oil sands and heavy crude oils surface and sub-surface production and separation of the bitumen, tailings management:
Include surface and in-situ production (e.g., SAGD), tailings management.

In 2020, what were this organization's energy R&D expenditures on oil sands and heavy crude oil surface and sub-surface production and separation of bitumen, tailings management?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for fossil fuels within this reporting unit.

28. In 2020, what were this organization's energy R&D expenditures on refining, processing and upgrading of fossil fuels?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2020, what were this organization's energy R&D expenditures on refining, processing and upgrading of fossil fuels?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for fossil fuels within this reporting unit.

29. In 2020, what were this organization's energy R&D expenditures on coal production, separation and processing?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2020, what were this organization's energy R&D expenditures on coal production, separation and processing?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for fossil fuels within this reporting unit.

30. In 2020, what were this organization's energy R&D expenditures on transportation of fossil fuels?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2020, what were this organization's energy R&D expenditures on transportation of fossil fuels?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Energy-related R&D by area of technology - Renewable energy resources

31. In 2020, did this organization's total in-house and outsourced (contracted out or granted) R&D expenditures include renewable energy resources-related R&D in the following categories?

Select all that apply.

Solar photovoltaics (PV):
Include solar cell development, PV-module development, PV-inverter development, building-integrated PV-modules, PV-system development, other.

Solar thermal-power and high-temperature applications:
Include solar chemistry, concentrating collector development, solar thermal power plants, high-temperature applications for heat and power.

Solar heating and cooling:
Include daylighting, passive and active solar heating and cooling, collector development, hot water preparation, combined-space heating, solar architecture, solar drying, solar-assisted ventilation, swimming pool heating, low-temperature process heating, other.

Wind energy:
Include technology development, such as blades, turbines, converters structures, system integration, other.

Bio-energy - Biomass production/supply and transport:
Include improvement of energy crops, research on bio-energy production potential and associated land-use effects, supply and transport of bio-solids, bio-liquids, biogas and bio-derived energy products (e.g., ethanol, biodiesel), compacting and baling, other.

Bio-energy - Biomass conversion to fuels:
Include conventional bio-fuels, cellulosic-derived alcohols, biomass gas-to-liquids, other energy-related products and by-products.

Bio-energy - Biomass conversion to heat and electricity:
Include bio-based heat, electricity and combined heat and power (CHP).
Exclude multi-firing with fossil fuels.

Other bio-energy:
Include recycling and the use of municipal, industrial and agricultural waste as energy not covered elsewhere.

Small hydro - (less than 10 MW):
Include plants with capacity below 10 MW.

Large hydro - (greater than or equal to 10 MW):
Include plants with capacity of 10 MW and above.

Other renewable energy:
Include hot dry rock, hydro-thermal, geothermal heat applications (including agriculture), tidal power, wave energy, ocean current power, ocean thermal power, other.

Solar photovoltaics (PV)
Solar thermal-power and high-temperature applications
Solar heating and cooling
Wind energy
Bio-energy - biomass production and transportation
Bio-energy - biomass conversion to transportation fuel
Bio-energy - biomass conversion to heat and electricity
Other bio-energy
Small hydro (less than 10 MW)
Large hydro (greater than or equal to 10 MW)
Other renewable energy
Include ocean and geothermal.
None of the above

Energy-related R&D by area of technology

Report all 2020 R&D expenditures for renewable energy resources within this reporting unit.

32. In 2020, what were this organization's energy R&D expenditures on solar photovoltaics (PV)?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Solar photovoltaics (PV):
Include solar cell development, PV-module development, PV-inverter development, building-integrated PV-modules, PV-system development, other.

In 2020, what were this organization's energy R&D expenditures on solar photovoltaics (PV)?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for renewable energy resources within this reporting unit.

33. In 2020, what were this organization's energy R&D expenditures on solar thermal-power and high-temperature applications?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Solar thermal-power and high-temperature applications:
Include solar chemistry, concentrating collector development, solar thermal power plants, high-temperature applications for heat and power.

In 2020, what were this organization's energy R&D expenditures on solar thermal-power and high-temperature applications?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for renewable energy resources within this reporting unit.

34. In 2020, what were this organization's energy R&D expenditures on solar heating and cooling?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2020, what were this organization's energy R&D expenditures on solar heating and cooling?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for renewable energy resources within this reporting unit.

35. In 2020, what were this organization's energy R&D expenditures on wind energy?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Wind energy:
Include technology development, such as blades, turbines, converters structures, system integration, other.

In 2020, what were this organization's energy R&D expenditures on wind energy?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for renewable energy resources within this reporting unit.

36. In 2020, what were this organization's energy R&D expenditures on bio-energy - biomass production and transport?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2020, what were this organization's energy R&D expenditures on bio-energy - biomass production and transport?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for renewable energy resources within this reporting unit.

37. In 2020, what were this organization's energy R&D expenditures on bio-energy - biomass conversion to transportation fuel?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Bio-energy - Biomass conversion to transportation fuel:
Include conventional bio-fuels, cellulosic-derived alcohols, biomass gas-to-liquids, other energy-related products and by-products.

In 2020, what were this organization's energy R&D expenditures on bio-energy - biomass conversion to transportation fuel?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for renewable energy resources within this reporting unit.

38. In 2020, what were this organization's energy R&D expenditures on bio-energy - biomass conversion to heat and electricity?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Bio-energy - Biomass conversion to heat and electricity:
Include bio-based heat, electricity and combined heat and power (CHP).
Exclude multi-firing with fossil fuels.

In 2020, what were this organization's energy R&D expenditures on bio-energy - biomass conversion to heat and electricity?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for renewable energy resources within this reporting unit.

39. In 2020, what were this organization's energy R&D expenditures on other bio-energy?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Other bio-energy:
Include recycling and the use of municipal, industrial and agricultural waste as energy not covered elsewhere.

In 2020, what were this organization's energy R&D expenditures on other bio-energy?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for renewable energy resources within this reporting unit.

40. In 2020, what were this organization's energy R&D expenditures on small hydro (less than 10 MW)?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Small hydro - (less than 10 MW):
Include plants with capacity below 10 MW.

In 2020, what were this organization's energy R&D expenditures on small hydro (less than 10 MW)?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for renewable energy resources within this reporting unit.

41. In 2020, what were this organization's energy R&D expenditures on large hydro (greater than or equal to 10 MW)?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Large hydro - (greater than or equal to 10 MW):
Include plants with capacity of 10 MW or greater.

In 2020, what were this organization's energy R&D expenditures on large hydro (greater than or equal to 10 MW)?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for renewable energy resources within this reporting unit.

42. In 2020, what were this organization's energy R&D expenditures on other renewable energy?

Include ocean and geothermal.

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Other renewable energy:
Include hot dry rock, hydro-thermal, geothermal heat applications (including agriculture), tidal power, wave energy, ocean current power, ocean thermal power, other.

In 2020, what were this organization's energy R&D expenditures on other renewable energy?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Energy-related R&D by area of technology - Nuclear fission and fusion

43. In 2020, did this organization's total in-house and outsourced (contracted out or granted) R&D expenditures include nuclear fission and fusion-related R&D in the following categories?

Select all that apply.

Exploration, mining and preparation, tailings management:
Include development of advanced exploration methods (geophysical, geochemical) for prospecting, ore surface and in-situ production, uranium and thorium extraction and conversion, enrichment, handling of tailings and remediation.

Nuclear reactors:
Include nuclear reactors of all types and related system components.

Other fission:
Include nuclear safety, environmental protection (emission reduction or avoidance), radiation protection and decommissioning of power plants and related nuclear fuel cycle installations, nuclear waste treatment, disposal and storage, fissile material recycling, fissile materials control, transport of radioactive materials.

Fusion:
Include all types (e.g., magnetic confinement, laser applications).

Nuclear materials exploration, mining and preparation, tailings management
Nuclear reactors
Other fission
Fusion
None of the above

Energy-related R&D by area of technology

Report all 2020 R&D expenditures for nuclear fission and fusion within this reporting unit.

44. In 2020, what were this organization's energy R&D expenditures on nuclear materials exploration, mining and preparation, tailings management?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2020, what were this organization's energy R&D expenditures on nuclear materials exploration, mining and preparation, tailings management?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for nuclear fission and fusion within this reporting unit.

45. In 2020, what were this organization's energy R&D expenditures on nuclear reactors?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Nuclear reactors:
Include nuclear reactors of all types and related system components.

In 2020, what were this organization's energy R&D expenditures on nuclear reactors?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for nuclear fission and fusion within this reporting unit.

46. In 2020, what were this organization's energy R&D expenditures on other fission?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2020, what were this organization's energy R&D expenditures on other fission?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for nuclear fission and fusion within this reporting unit.

47. In 2020, what were this organization's energy R&D expenditures on fusion?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Fusion:
Include all types (e.g., magnetic confinement, laser applications).

In 2020, what were this organization's energy R&D expenditures on fusion?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Energy-related R&D by area of technology - Electric power

48. In 2020, did this organization's total in-house and outsourced (contracted out or granted) R&D expenditures include electric power-related R&D in the following categories?

Select all that apply.

Electric power generation in utility sector:
Include conventional and non-conventional technology (e.g., pulverised coal, fluidised bed, gasification-combined cycle, supercritical), re-powering, retrofitting, life extensions and upgrading of power plants, generators and components, super-conductivity, magneto hydrodynamic, dry cooling towers, co-firing (e.g., with biomass), air and thermal pollution reduction or avoidance, flue gas cleanup (excluding CO2 removal), CHP (combined heat and power) not covered elsewhere.

Electric power - combined heat and power in industry, buildings:
Include industrial applications, small scale applications for buildings.

Electricity transmission, distribution and storage:
Include solid state power electronics, load management and control systems, network problems, super-conducting cables, AC and DC high voltage cables, HVDC transmission, other transmission and distribution related to integrating distributed and intermittent generating sources into networks, all storage (e.g., batteries, hydro reservoirs, fly wheels), other.

Electric power generation in utility sector
Electric power - combined heat and power in industry, buildings
Electricity transmission, distribution and storage
None of the above

Energy-related R&D by area of technology

Report all 2020 R&D expenditures for electric power within this reporting unit.

49. In 2020, what were this organization's energy R&D expenditures on electric power generation in utility sector?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2020, what were this organization's energy R&D expenditures on electric power generation in utility sector?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for electric power within this reporting unit.

50. In 2020, what were this organization's energy R&D expenditures on electric power - combined heat and power in industry, buildings?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Electric power - combined heat and power in industry, buildings:
Include industrial applications, small scale applications for buildings.

In 2020, what were this organization's energy R&D expenditures on electric power - combined heat and power in industry, buildings?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for electric power within this reporting unit.

51. In 2020, what were this organization's energy R&D expenditures on electricity transmission, distribution and storage?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2020, what were this organization's energy R&D expenditures on electricity transmission, distribution and storage?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Energy-related R&D by area of technology - Hydrogen and fuel cells

52. In 2020, did this organization's total in-house and outsourced (contracted out or granted) R&D expenditures include hydrogen and fuel cells-related R&D in the following categories?

Select all that apply.

Other hydrogen:
Include end uses (e.g., combustion), other infrastructure and systems R&D (refuelling stations).

Stationary fuel cells:
Include electricity generation, other stationary end-use.

Mobile fuel cell:
Include portable applications.

Hydrogen production for process applications
Hydrogen production for transportation applications
Hydrogen transport and storage
Other hydrogen
Stationary fuel cells
Mobile fuel cells
None of the above

Energy-related R&D by area of technology

Report all 2020 R&D expenditures for hydrogen and fuel cells within this reporting unit.

53. In 2020, what were this organization's energy R&D expenditures on hydrogen production for process applications?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2020, what were this organization's energy R&D expenditures on hydrogen production for process applications?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for hydrogen and fuel cells within this reporting unit.

54. In 2020, what were this organization's energy R&D expenditures on hydrogen production for transportation applications?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2020, what were this organization's energy R&D expenditures on hydrogen production for transportation applications?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for hydrogen and fuel cells within this reporting unit.

55. In 2020, what were this organization's energy R&D expenditures on hydrogen transport and storage?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2020, what were this organization's energy R&D expenditures on hydrogen transport and storage?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for hydrogen and fuel cells within this reporting unit.

56. In 2020, what were this organization's energy R&D expenditures on other hydrogen?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Other hydrogen:
Include end uses (e.g., combustion), other infrastructure and systems R&D (refuelling stations).

In 2020, what were this organization's energy R&D expenditures on other hydrogen?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for hydrogen and fuel cells within this reporting unit.

57. In 2020, what were this organization's energy R&D expenditures on stationary fuel cells?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Stationary fuel cells:
Include electricity generation, other stationary end-use.

In 2020, what were this organization's energy R&D expenditures on stationary fuel cells?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for hydrogen and fuel cells within this reporting unit.

58. In 2020, what were this organization's energy R&D expenditures on mobile fuel cells?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Mobile fuel cells:
Include portable applications.

In 2020, what were this organization's energy R&D expenditures on mobile fuel cells?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Energy-related R&D by area of technology - Energy efficiency

59. In 2020, did this organization's total in-house and outsourced (contracted out or granted) R&D expenditures include energy efficiency-related R&D in the following categories?

Select all that apply.

Energy efficiency for industry:
Include reduction of energy consumption through improved use of energy and/or reduction or avoidance of air and other emissions related to the use of energy in industrial systems and processes (excluding bio-energy-related) through the development of new techniques, new processes and new equipment, other.

Energy efficiency for residential, institutional and commercial:
Include space heating and cooling, ventilation and lighting control systems other than solar technologies, low energy housing design and performance other than solar technologies, new insulation and building materials, thermal performance of buildings, domestic appliances, other.

Energy efficiency for transportation:
Include analysis and optimisation of energy consumption in the transport sector, efficiency improvements in light-duty vehicles, heavy-duty vehicles, non-road vehicles, public transport systems, engine-fuel optimisation, use of alternative fuels (liquid and gaseous, other than hydrogen), fuel additives, diesel engines, Stirling motors, electric cars, hybrid cars, air emission reduction, other.

Other energy efficiency:
Include waste heat utilisation (heat maps, process integration, total energy systems, low temperature thermodynamic cycles), district heating, heat pump development, reduction of energy consumption in the agricultural sector.

Energy efficiency applications for industry
Energy efficiency for residential, institutional and commercial sectors
Energy efficiency for transportation
Other energy efficiency
None of the above

Energy-related R&D by area of technology

Report all 2020 R&D expenditures for energy efficiency within this reporting unit.

60. In 2020, what were this organization's energy R&D expenditures on energy efficiency applications for industry?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2020, what were this organization's energy R&D expenditures on energy efficiency applications for industry?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for energy efficiency within this reporting unit.

61. In 2020, what were this organization's energy R&D expenditures on energy efficiency for residential, institutional and commercial sectors?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2020, what were this organization's energy R&D expenditures on energy efficiency for residential, institutional and commercial sectors?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for energy efficiency within this reporting unit.

62. In 2020, what were this organization's energy R&D expenditures on energy efficiency for transportation?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2020, what were this organization's energy R&D expenditures on energy efficiency for transportation?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for energy efficiency within this reporting unit.

63. In 2020, what were this organization's energy R&D expenditures on other energy efficiency?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2020, what were this organization's energy R&D expenditures on other energy efficiency?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Energy-related R&D by area of technology - Other energy-related technologies

64. In 2020, did this organization's total in-house and outsourced (contracted out or granted) R&D expenditures include other energy-related R&D in the following categories?

Select all that apply.

Carbon capture end-use:
Include industry in the end-use sector, such as steel production, manufacturing, etc. (exclude fossil fuel production and processing and electric power production).

Energy system analysis:
Include system analysis related to energy R&D not covered elsewhere, sociological, economical and environmental impact of energy which are not specifically related to one technology area listed in the sections above.

All other energy technologies:
Include energy technology information dissemination, studies not related to a specific technology area listed above.

Carbon capture, transport and storage related to fossil fuel production and processing
Carbon capture, transport and storage related to electric power production
Carbon capture, transport and storage related to industry in end-use sector
Energy system analysis
All other energy-related technologies
None of the above

Energy-related R&D by area of technology

Report all 2020 R&D expenditures for other energy-related technologies within this reporting unit.

65. In 2020, what were this organization's energy R&D expenditures on carbon capture, transport and storage related to fossil fuel production and processing?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2020, what were this organization's energy R&D expenditures on carbon capture, transport and storage related to fossil fuel production and processing?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for other energy-related technologies within this reporting unit.

66. In 2020, what were this organization's energy R&D expenditures on carbon capture, transport and storage related to electric power production?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2020, what were this organization's energy R&D expenditures on carbon capture, transport and storage related to electric power production?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for other energy-related technologies within this reporting unit.

67. In 2020, what were this organization's energy R&D expenditures on carbon capture, transport and storage related to industry in end-use sector?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Carbon capture end-use:
Include industry in the end-use sector, such as steel production, manufacturing, etc. (exclude fossil fuel production and processing and electric power production).

In 2020, what were this organization's energy R&D expenditures on carbon capture, transport and storage related to industry in end-use sector?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for other energy-related technologies within this reporting unit.

68. In 2020, what were this organization's energy R&D expenditures on energy system analysis?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

In 2020, what were this organization's energy R&D expenditures on energy system analysis?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Report all 2020 R&D expenditures for other energy-related technologies within this reporting unit.

69. In 2020, what were this organization's energy R&D expenditures on other energy-related technologies?

Exclude capital depreciation.

Please report all amounts in thousands of Canadian dollars.

Report '0' for no R&D expenditures.

Other energy-related technologies:
Include energy technology information dissemination, studies not related to a specific technology area listed above.

In 2020, what were this organization's energy R&D expenditures on other energy-related technologies?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	CAN$ '000
Funds from this organization
Funds from federal, provincial or territorial government(s)
All other Canadian sources of funds
All foreign sources of funds
Total in-house R&D
Outsourced (contracted out or granted) within Canada
Outsourced (contracted out or granted) outside Canada
Total outsourced R&D

Summary of energy-related and total R&D expenditures

70. Summary of total 2020 energy-related R&D and total R&D expenditures

Please review the values and if needed, press the 'Previous' button at the bottom of the page to navigate to the previous pages to make any modifications.

Summary of total 2020 energy-related R&D and total R&D expenditures
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	Total energy-related R&D	Total R&D
Total funds from this organization
Total funds from federal, provincial or territorial government(s)
Total all other Canadian sources of funds
Total all foreign sources of funds
Total in-house R&D expenditures
Total outsourced (contracted out or granted) within Canada
Total outsourced (contracted out or granted) outside Canada
Total outsourced (contracted out or granted) R&D expenditures
Total R&D expenditures

In-house R&D personnel in 2020

71. In 2020, how many in-house R&D personnel within Canada did this organization have in the following R&D occupations?

Full-time equivalent (FTE)

R&D may be carried out by persons who work solely on R&D projects or by persons who devote only part of their time to R&D, and the balance to other activities such as testing, quality control and production engineering. To arrive at the total effort devoted to R&D in terms of personnel, it is necessary to estimate the full-time equivalent of these persons working only part-time in R&D.

Full-time equivalent (FTE) = Number of persons who work solely on R&D projects + the time of persons working only part of their time on R&D.

Example calculation: If out of four scientists engaged in R&D work, one works solely on R&D projects and the remaining three devote only one quarter of their working time to R&D, then: FTE = 1 + 1/4 + 1/4 + 1/4 = 1.75 scientists.

R&D personnel

Include:

permanent, temporary and casual R&D employees
independent on-site R&D consultants and contractors working in your organization's offices, laboratories, or other facilities
employees engaged in R&D -related support activities.

Researchers and research managers are composed of:

Scientists, social scientists, engineers and researchers are professionals engaged in the conception or creation of new knowledge. They conduct research and improve or develop concepts, theories, models, techniques instrumentation, software or operational methods. They may be certified by provincial or territorial educational authorities, provincial, territorial or national scientific or engineering associations.
Senior research managers plan or manage R&D projects and programs. They may be certified by provincial or territorial educational authorities, provincial, territorial or national scientific or engineering associations.

R&D technical, administrative and support staff are composed of:

Technicians and technologists and research assistants are persons whose main tasks require technical knowledge and experience in one or more fields of engineering, the physical and life sciences, or the social sciences, humanities and the arts. They participate in R&D by performing scientific and technical tasks involving the application of concepts, operational methods and the use of research equipment, normally under the supervision of researchers. They may be certified by provincial or territorial educational authorities, provincial, territorial or national scientific or engineering associations.
Other R&D technical, administrative support staff include skilled and unskilled craftsmen, and administrative, secretarial and clerical staff participating in R&D projects or directly associated with such projects.

On-site R&D consultants and contractors are individuals hired 1) to perform project-based work or to provide goods at a fixed or ascertained price or within a certain time or 2) to provide advice or services in a specialized field for a fee and, in both cases, work at the location specified and controlled by the contracting company or organization.

In 2020, how many in-house R&D personnel within Canada did this organization have in the following R&D occupations?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	Number of full-time equivalents (FTE)
Researchers and research managers
Scientists, social scientists, engineers and researchers
Senior research managers
Total researchers and research managers
R&D technical, administrative and support staff
Technicians, technologists and research assistants
Other R&D technical, administrative and support staff
Total R&D technical, administrative and support staff
Other R&D occupations
On-site R&D consultants and contractors
Total in-house R&D personnel within Canada

72. Of this organization's total in-house R&D personnel reported above, what percentage performed software-related activities?

Software-related sciences and technologies

Software engineering and technology: computer software engineering, computer software technology and other related computer software engineering and technologies.
Computer sciences: computer science, artificial intelligence, cryptography and other related computer sciences.
Information technology and bioinformatics: information technology, informatics, bioinformatics, biomathematics and other related information technologies.

Percentage of software-related activities

73. In 2020, how were the total [Amount] in-house R&D personnel distributed by province or territory?

Please report in full-time equivalents (FTE).

R&D personnel

Include:

permanent, temporary and casual R&D employees
independent on-site R&D consultants and contractors working in your organization's offices, laboratories, or other facilities
employees engaged in R&D -related support activities.

Researchers and research managers are composed of:

Scientists, social scientists, engineers and researchers are professionals engaged in the conception or creation of new knowledge. They conduct research and improve or develop concepts, theories, models, techniques instrumentation, software or operational methods. They may be certified by provincial or territorial educational authorities, provincial, territorial or national scientific or engineering associations.
Senior research managers plan or manage R&D projects and programs. They may be certified by provincial or territorial educational authorities, provincial, territorial or national scientific or engineering associations.

R&D technical, administrative and support staff are composed of:

Technicians and technologists and research assistants are persons whose main tasks require technical knowledge and experience in one or more fields of engineering, the physical and life sciences, or the social sciences, humanities and the arts. They participate in R&D by performing scientific and technical tasks involving the application of concepts, operational methods and the use of research equipment, normally under the supervision of researchers. They may be certified by provincial or territorial educational authorities, provincial, territorial or national scientific or engineering associations.
Other R&D technical, administrative support staff include skilled and unskilled craftsmen, and administrative, secretarial and clerical staff participating in R&D projects or directly associated with such projects.

Full-time equivalent (FTE)

Full-time equivalent (FTE) = Number of persons who work solely on R&D projects + the time of persons working only part of their time on R&D.

In 2020, how were the total [Amount] in-house R&D personnel distributed by province or territory?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	Number of researchers and research managers	Number of R&D technical, administrative and support staff	Number of on-site R&D consultants and contractors
Newfoundland and Labrador
Prince Edward Island
Nova Scotia
New Brunswick
Quebec
Ontario
Manitoba
Saskatchewan
Alberta
British Columbia
Yukon
Northwest Territories
Nunavut
Total in-house R&D personnel within Canada
Total R&D personnel previously reported from question 71

Technology and technical assistance payments in 2020

74. In 2020, did this organization make or receive payments inside or outside Canada for the following technology and technical assistance?

Technology and technical assistance payments

Definitions (equivalent to the Canadian Intellectual Property Office Canadian Intellectual Property Office - opens in a new browser window):

Patent
Government grant giving the right to exclude others from making, using or selling an invention.
Copyright
Legal protection for literary, artistic, dramatic or musical works, computer programs, performer's performances, sound recordings, and communication signals.
Trademark
A word, symbol or design, or combination of these, used to distinguish goods or services of one person or organization from those of others in the marketplace.
Industrial design
Legal protection against imitation of the shape, pattern, or ornamentation of an object.
Integrated circuit topography
Three-dimensional configurations of the elements and interconnections embodied in an integrated circuit product.
Original software
Computer programs and descriptive materials for both systems and applications. Original software can be created in-house or outsourced and includes packaged software with customization.
Packaged or off-the-shelf software
Packaged software purchased for organizational use and excludes software with customization.
Databases
Data files organized to permit effective access and use of the data including access clinical trial registries and administrative health data for research purposes. Includes partnerships supporting the development of databases, such as patient or clinical trial registries or biobanks, to be used for research purposes (e.g., developing a national bladder cancer patient registry with Bladder Cancer Canada for future research).
Other
Technical assistance, industrial processes and know-how including technology transfer and know how such as batch pilot production, method develop, and validation related to technology or manufacturing transfer.

In 2020, did this organization make or receive payments inside or outside Canada for the following technology and technical assistance?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	Made Payments	Received Payments	Both made and received payments	Not applicable
Patents
Copyrights
Trademarks
Industrial design
Integrated circuit topography
Original software
Packaged or off-the-shelf software
Databases
Other technology and technical assistance

75. In 2020, how much did this organization pay to other organizations for technology and technical assistance?

Please report all amounts in thousands of Canadian dollars.

Report '1' for payments made between $1 and $999.

Technology and technical assistance payments

Definitions (equivalent to the Canadian Intellectual Property Office Canadian Intellectual Property Office - opens in a new browser window):

Patent
Government grant giving the right to exclude others from making, using or selling an invention.
Copyright
Legal protection for literary, artistic, dramatic or musical works, computer programs, performer's performances, sound recordings, and communication signals.
Trademark
A word, symbol or design, or combination of these, used to distinguish goods or services of one person or organization from those of others in the marketplace.
Industrial design
Legal protection against imitation of the shape, pattern, or ornamentation of an object.
Integrated circuit topography
Three-dimensional configurations of the elements and interconnections embodied in an integrated circuit product.
Original software
Computer programs and descriptive materials for both systems and applications. Original software can be created in-house or outsourced and includes packaged software with customization.
Packaged or off-the-shelf software
Packaged software purchased for organizational use and excludes software with customization.
Databases
Data files organized to permit effective access and use of the data including access clinical trial registries and administrative health data for research purposes. Includes partnerships supporting the development of databases, such as patient or clinical trial registries or biobanks, to be used for research purposes (e.g., developing a national bladder cancer patient registry with Bladder Cancer Canada for future research).
Other
Technical assistance, industrial processes and know-how including technology transfer and know how such as batch pilot production, method develop, and validation related to technology or manufacturing transfer.

In 2020, how much did this organization pay to other organizations for technology and technical assistance?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	Payments made within Canada CAN$ '000	Payments made outside Canada CAN$ '000
Payments made to members, affiliated companies or organizations
Patents
Copyrights
Trademarks
Industrial design
Integrated circuit topography
Original software
Packaged or off-the-shelf software
Databases
Other technology and technical assistance
Total payments made to members, affiliated companies or organizations
Payments made to other organizations, companies or individuals
Patents
Copyrights
Trademarks
Industrial design
Integrated circuit topography
Original software
Packaged or off-the-shelf software
Databases
Other technology and technical assistance
Total payments made to other organizations, companies or individuals
Total payments made to other organizations for technology and technical assistance

76. In 2020, how much did this organization receive from other organizations for technology and technical assistance?

Please report all amounts in thousands of Canadian dollars.

Report '1' for payments received between $1 and $999.

Technology and technical assistance payments

Definitions (equivalent to the Canadian Intellectual Property Office Canadian Intellectual Property Office - opens in a new browser window):

Patent
Government grant giving the right to exclude others from making, using or selling an invention.
Copyright
Legal protection for literary, artistic, dramatic or musical works, computer programs, performer's performances, sound recordings, and communication signals.
Trademark
A word, symbol or design, or combination of these, used to distinguish goods or services of one person or organization from those of others in the marketplace.
Industrial design
Legal protection against imitation of the shape, pattern, or ornamentation of an object.
Integrated circuit topography
Three-dimensional configurations of the elements and interconnections embodied in an integrated circuit product.
Original software
Computer programs and descriptive materials for both systems and applications. Original software can be created in-house or outsourced and includes packaged software with customization.
Packaged or off-the-shelf software
Packaged software purchased for organizational use and excludes software with customization.
Databases
Data files organized to permit effective access and use of the data including access clinical trial registries and administrative health data for research purposes. Includes partnerships supporting the development of databases, such as patient or clinical trial registries or biobanks, to be used for research purposes (e.g., developing a national bladder cancer patient registry with Bladder Cancer Canada for future research).
Other
Technical assistance, industrial processes and know-how including technology transfer and know how such as batch pilot production, method develop, and validation related to technology or manufacturing transfer.

In 2020, how much did this organization receive from other organizations for technology and technical assistance?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	Payments received from within Canada CAN$ '000	Payments received from outside Canada CAN$ '000
Payments received from members, affiliated companies or organizations
Patents
Copyrights
Trademarks
Industrial design
Integrated circuit topography
Original software
Packaged or off-the-shelf software
Databases
Other technology and technical assistance
Total payments received from members, affiliated companies or organizations
Payments received from other organizations, companies or individuals
Patents
Copyrights
Trademarks
Industrial design
Integrated circuit topography
Original software
Packaged or off-the-shelf software
Databases
Other technology and technical assistance
Total payments received from other organizations, companies or individuals
Total payments received from other organizations for technology and technical assistance

Environmental and clean technology R&D expenditures in 2020

77. In 2020, what percentage of this organization's total expenditures of $ [Amount] for R&D performed in-house within Canada was related to research and development of environmental and clean technologies?

Environmental and clean technology is defined as any process, product, or service that reduces environmental impacts: through environmental protection activities that prevent, reduce or eliminate pollution or any other degradation of the environment, resource management activities that result in the more efficient use of natural resources, thus safeguarding against their depletion; or the use of goods that have been adapted to be significantly less energy- or resource-intensive than the industry standard.

Report '0' for no environmental and clean technology R&D expenditures.

If precise figures are not available, please provide your best estimate.

Percentage of environmental and clean technology R&D

78. In 2020, in which of the following categories of environmental and clean technology did this organization perform R&D activities?

Select all that apply.

Air pollution management: Activities aimed at reducing the emissions of pollutants (including greenhouse gases) to the atmosphere. Include pollution abatement and control (e.g., end-of-pipe processes) and pollution prevention (e.g., integrated processes), as well as related measurement, control, laboratories and the like.

Solid waste management: Activities related to the collection, treatment, storage, disposal, and recycling of all domestic, industrial, non-hazardous and hazardous waste (including low-level radioactive waste). Include monitoring activities. Exclude radioactive waste and mine tailings handling and treatment (to be reported under Protection against radiation and Wastewater management, respectively).

Wastewater management: Activities aimed at pollution reduction or prevention through the abatement of pollutants or the reduction of the release of wastewater. Include measures aimed at reducing pollutants before discharge, reducing the release of wastewater, septic tanks, treatment of cooling water, handling and treatment of mine tailings, etc.

Protection and remediation of soil, groundwater and surface water: Activities aimed at the prevention of pollution infiltration: remediation or cleaning up of soils and water bodies; protection of soil from erosion, salinization and physical degradation; monitoring, control, laboratories and the like. Exclude management of wastewater released to surface waters, municipal sewer systems or soil, or injected underground (to be reported under Wastewater management) and protection of biodiversity and habitat (to be reported under Protection of biodiversity and habitat).

Protection of biodiversity and habitat: Activities related to protecting wildlife and habitat from the effects of economic activity, and to restoring wildlife or habitat that has been adversely affected by such activity. Include related environmental measurements, monitoring, control, laboratories and the like.

Noise and vibration abatement: Activities aimed at controlling or reducing industrial and transport noise and vibration for the sole purpose of protecting the environment. Include preventive in-process modifications at the source, construction of anti-noise/vibration facilities, measurement, control, laboratories and the like.

Protection against radiation: Activities aimed at preventing, reducing, or eliminating the negative consequences of radiation on the environment. This includes all handling, transportation, and treatment of radioactive waste (i.e., waste that requires shielding during normal handling and transportation due to high radionuclide content), the protection of ambient media, measurement, control, laboratories and the like, as well as any other activities related to the containment of radioactive waste. Exclude activities and measures related to low-level radioactive waste (to be reported under Solid waste management), the prevention of technological hazards (e.g., external safety of nuclear power plants), and measures taken to protect workers.

Heat or energy savings and management: Activities aimed at reducing the intake of energy through in-process modifications (such as adjustment of production processes or heat and electricity co-generation), as well as reducing heat and energy losses. This includes insulation activities, energy recovery, measurement, control, laboratories and the like.

Renewable energy: Energy obtained from resources that naturally replenish or renew within a human lifespan (i.e., the resource is a sustainable source of energy). This includes wind, solar, aero-thermal, geothermal, hydrothermal and ocean energy, hydropower, biomass, landfill gas, sewage treatment plant gas and biogases.

Air pollution management
e.g., greenhouse gas control technologies or management services, physical or chemical treatment technologies, air pollution modeling and mapping services
Solid waste management
e.g., collection of waste, recycling and organics, compaction-related technologies, landfill leachate collection and containment technologies
Wastewater management
e.g., physical or chemical treatments of industrial wastewater, mine tailing handling and treatment, biological treatments of sewage
Protection and remediation of soil, groundwater and surface water
e.g., in situ and ex situ biological, physical, chemical, thermal treatments, containment
Protection of biodiversity and habitat
Noise and vibration abatement
Exclude R&D related to workers' health and safety.
Protection against radiation
Exclude R&D related to workers' health and safety.
Heat and energy savings and management
e.g., efficient equipment (advance insulation, high efficiency pumps or burners (Energy Star certified, etc.), energy storage technologies (flywheels, fuel cells, etc.), lighting upgrades, smart grid services and associated technologies
Fuel efficient vehicles and transportation goods or technologies
e.g., electric and hybrid vehicles, vehicles using alternative fuels, alternative fuel retrofits on existing vehicles, low-rolling resistance tires
Production of energy from renewable sources
e.g., equipment, services, and technologies used to produce electricity or heat from renewable sources
Production of nuclear energy
e.g., equipment, services, and technologies used to produce electricity or heat from nuclear energy
Exclude the R&D for feedstock used to produce energy (such as uranium).
Other environmental protection or resource management activities
Specify the other environmental protection or resource management activities

Changes in R&D activities due to COVID-19

COVID-19 has resulted in major economic changes, as businesses reacted to a general shutdown that started in Canada in mid-March 2021.

79. As a result of COVID-19, has this organization made any changes in research and development (R&D) activities or expenditures in 2020?

Changes in in-house R&D expenditures due to COVID-19

80. In response to the COVID-19 pandemic, did this organization modify its in-house R&D expenditures in Canada in 2020?

When precise figures are not available, please provide your best estimates.

Yes, increased in-house R&D expenditures

Please indicate the amount expenditures increased from previously planned expenditures due to COVID-19.

CAN$ '000

Yes, decreased in-house R&D expenditures

Please indicate the amount expenditures decreased from previously planned expenditures due to COVID-19.

CAN$ '000

No change in in-house R&D expenditures due to COVID-19
Do not know

COVID-19 related in-house R&D projects and sources of funds

81. In response to the COVID-19 pandemic, did this organization perform in-house R&D on COVID-19 related R&D projects in 2020?

COVID-19 related R&D: e.g., R&D to create self-sterilizing work surfaces; R&D to develop a COVID-19 diagnostic test; R&D to adapt LEDs to UV for light-weight air purification system, etc.

Yes
No
Do not know

82. In 2020, how much funding did this organization receive from each of the following sources to undertake COVID-19 related in-house R&D projects?

Include self-funding.

Include COVID-19 related funds that have been applied for, which this business organization hopes to receive.

When precise figures are not available, please provide your best estimates.

In 2020, how much funding did this business organization receive or does it expect to receive from each of the following sources to undertake COVID-19 related in-house R&D projects?
Table summary
This table contains no data. It is an example of an empty data table used by respondents to provide data to Statistics Canada.
	Amount of funding received CAN$ '000
All funding for COVID-19 projects by source
Self-funded
Companies
Federal government
Provincial and territorial government
Private non-profit organizations
Postsecondary institutions e.g. universities colleges
Other Canadian sources
Foreign sources
Total funding for COVID-19 related R&D projects

Changes in R&D personnel due to COVID-19

83. In response to the COVID-19 pandemic, were there any net changes to the number of full-time equivalent (FTEs) R&D personnel employed or contracted in 2020 by this business?

When precise figures are not available, please provide your best estimates.

Yes, increased in FTEs

How many more R&D personnel (FTE)s were hired or contracted due to COVID-19?

Number of full-time equivalents

Yes, decreased in FTEs

How many fewer R&D personnel (FTE)s were employed due to COVID-19?

Number of full-time equivalents

No change in R&D personnel due to COVID-19
Do not know

Changes in outsourced R&D expenditures due to COVID-19

84. In response to the COVID-19 pandemic, did this organization modify its outsourced R&D expenditures in 2020?

When precise figures are not available, please provide your best estimates.

Yes, increased outsourced R&D expenditures

Please indicate the amount expenditures increased from previously planned expenditures due to COVID-19.

CAN$ '000

Yes, decreased outsourced R&D expenditures

Please indicate the amount expenditures decreased from previously planned expenditures due to COVID-19.

CAN$ '000

No change in payments made to other organizations for R&D due to COVID-19
Do not know

Notification of intent to extract web data

85. Does this organization have a website?

Yes
- Specify the business website address
- e.g., www.example.ca
No

Notification of intent to extract web data

Statistics Canada is piloting a web data extraction initiative, also known as web scraping, which uses software to search and compile publicly available data from organizational websites. As a result, we may visit the website for this organization to search for, and compile, additional information. This initiative should allow us to reduce the reporting burden on organizations, as well as produce additional statistical indicators to ensure that our data remain accurate and relevant.

We will do our utmost to ensure the data are collected in a manner that will not affect the functionality of the website. Any data collected will be used by Statistics Canada for statistical and research purposes only, in accordance with the agency's mandate.

Please visit Statistics Canada's web scraping initiative page for more information.

Please visit Statistics Canada's transparency and accountability page to learn more.

If you have any questions or concerns, please contact Statistics Canada Client Services, toll-free at 1-877-949-9492 (TTY: 1-800-363-7629) or by email at infostats@statcan.gc.ca. Additional information about this survey can be found by selecting the following link:

Information for survey participants (ISP)

Changes or events

86. Indicate any changes or events that affected the reported values for this business or organization, compared with the last reporting period.

Select all that apply.

Outsourcing of R&D project(s)
Initiation of new R&D project(s)
Completion of existing R&D project(s)
Major change in funding of R&D project(s) (loss of funding)
Major change in funding of R&D project(s) (increase in funding)
Organizational change that affected R&D activities (expansion, reduction, restructuring)
Economic change that affected R&D activities
Lack of availability of qualified R&D personnel
Other
Specify the other changes or events:
No changes or events

Contact person

87. Statistics Canada may need to contact the person who completed this questionnaire for further information.

Is the provided given names and the provided family name the best person to contact?

Who is the best person to contact about this questionnaire?

First name:
Last name:
Title:
Email address:
Telephone number (including area code):
Extension number (if applicable):
The maximum number of characters is 5.
Fax number (including area code):

Feedback

88. How long did it take to complete this questionnaire?

Include the time spent gathering the necessary information.

Hours:
Minutes:

89. Do you have any comments about this questionnaire?

2021 submissions

General Social Survey on Families linkage to tax (001-2021)

Purpose: The two primary objectives of the General Social Survey (GSS) are: to gather data on social trends in order to monitor changes in the living conditions and well-being of Canadians over time; and to provide information on specific social policy issues of current or emerging interest. Each year the GSS focuses on a different topic, such as family, victimization, social support and aging, and time use. A specific topic is usually repeated approximately every 5 years. The 2017 GSS focused on Families: it is the sixth iteration of a series of surveys which began in 1990.

The 2017 GSS on Families was previously linked to 2016 tax records to add personal and household income (reference number 008-2017). The existing linkage will be enhanced to include additional variables from the 2016 tax records. Linking to the tax files will ensure better quality data, lower respondent burden and decreased costs.

Output: The availability of the updated 2017 GSS-T1FF Analytical Data File will be announced in The Daily. The file will be made available to Statistics Canada researchers and to deemed employees at the Statistics Canada Research Data Centres. All data will remain confidential and protected under the Statistics Act.

Linkage of the Canadian Health Measures Survey (CHMS) to Adverse Health Outcomes and Cancer data (002-2021)

Purpose: The purpose of this project is the creation of the dataset to be used to assess the links between exposure to environmental chemicals and health outcomes resulting from the CHMS survey files being linked to adverse health outcomes and cancer data. Specifically, for each environmental chemical measured in the CHMS and adverse health outcomes, the extent of the association will be examined. Such an outcome file currently does not exist and is much needed to identify and mitigate health risks to Canadians.

Output: nalytical datasets will be placed in the Research Data Centres (RDCs) and access will be granted following standard RDC approval process. The source datasets will be anonymized and will respect variable restrictions in effect for the source datasets (e.g., hospital, vital statistics, cancer, tax files). Major findings will be used to create research papers for publication in peer-reviewed journals and presentations at workshops and conferences.

Predictors of Arsenic on Cancer Incidence within the Canadian Population (003-2021)

Purpose: The purpose of this project is to create a series of outcome files resulting from the Canadian Health Measures Survey (CHMS) files being linked to cancer data. These files will be used to identify the status and predictors of arsenic, within the Canadian population using results from the CHMS survey. Additionally, this project aims to perform a linkage to the Canadian Cancer Registry to determine the relationship between cancer risk and circulating arsenic levels, stratifying by arsenic metabolite and cancer subtype.

Output: Only aggregate data that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. Analytical datasets will be placed in the Research Data Centres (RDCs) and access will be granted following standard RDC approval process. The source datasets will be anonymized and will respect variable restrictions in effect for the source datasets (e.g., hospital, vital statistics, cancer, tax files). Major findings will be used to create research papers for publication in peer-reviewed journals and presentations at workshops and conferences.

GaitWay: Algorithms Predicting Adverse Health Outcomes in Multimorbid Populations (004-2021)

Purpose: The purpose of this project is to create an integrated analytical dataset that will enable researchers to develop a tool (i.e., algorithms) for predicting healthcare outcomes such as hospitalizations and death among older Canadians (aged 50 and older) living with two or more chronic diseases (i.e., multimorbid populations). Such a prediction tool would improve the way of studying chronic diseases together and provide a comprehensive view of the burden of multimorbidity in the population. The Canadian Health Measures Survey will be integrated with the Discharge Abstract Database and the Vital Statistics—Death Database to create the analytical dataset.

Output: The de-identified integrated data will be available to deemed employees to use in Research Data Centres. All data and analytical products to be released outside of Statistics Canada will conform to the confidentiality provisions of the Statistics Act. To ensure maximum benefit to the public, findings will be published in peer-reviewed journals and develop publicly accessible online calculators, hosted on the research team's knowledge translation platform ProjectBigLife.ca.

Canadian Forces Cancer and Mortality Study II (CF CAMS II) and the Veteran Suicide Mortality Study (VSMS) (005-2021)

Purpose: Canadian Forces (CF) are tasked with protecting Canada and its citizens from threats to security. CF members may be involved in combat, peace-keeping and observer missions, post-conflict peace building and humanitarian assistance. The very nature of these operations can pose unusual and uncommon exposures with known and unknown risks. Adverse outcomes, including death, may be immediate or delayed. In order to identify risks, Department of National Defence (DND) and Veterans Affairs Canada (VAC) must be able to conduct on-going analysis and interpretation of health information for CF personnel during and after their active military service period.

DND and VAC do not currently have access to complete information on mortality and cancer outcomes of serving and retired CF personnel.

The Canadian Forces Cancer and Mortality Study II, and the Veteran Suicide Mortality Study address major gaps in the health surveillance of CF personnel (serving and released). The general objectives of the studies are to describe the mortality and cancer experience in order to inform:

Health promotion and health protection policies and programs for serving personnel
Programs that deliver care for veterans (released), and their families.

Output: Only aggregate tabular statistics that conform to the confidentiality provisions of the Statistics Act and any applicable requirements of the Privacy Act will be released outside of Statistics Canada.

Findings from the Canadian Forces Cancer and Mortality Study, and the Veterans Suicide Mortality Study will be disseminated through DND and VAC publications, in peer-reviewed journals, through Veterans Associations publications and in scientific meetings/conferences. All information and reports will contain non-confidential aggregate statistics that will not result in the identification of individual members. If required, additional presentations of study results will be provided by the Canadian Forces Health Services Group at DND to CF leadership and employees; and by VAC's Research Directorate to the Department of Veterans Affairs' leadership and employees.

Profile of Homeless Shelters in Canada (006-2021)

Purpose: This project will link Employment and Social Development Canada's (ESDC's) homeless shelters list (National Service Provider List- NSPL) to Statistics Canada's Linkable File Environment (LFE) and will produce a set of custom-designed tables that will profile the financial and other characteristics of homeless shelters in Canada.

Output: The output will be a set of custom-designed tables that will profile homeless shelters in Canada by geographical location, industry, size, non-profit vs for-profit status, employment and key financial characteristics such as revenues, assets, profit, etc.

Record linkages for the 2021 Census of Population (007-2021)

Purpose: The purpose of this linkage project is to obtain specific detailed information to supplement or replace the data collected through the 2021 Census questionnaires and to improve overall the data quality of the Census Program. This use of record linkage provides better-quality, detailed information for small communities and populations, saves time and money, and ensures that the census remains accurate, relevant and efficient. By expanding the use of administrative data in the 2021 Census through record linkage, the burden of response is also reduced as Canadians are spared from supplying the same information they have already provided elsewhere.

Output: The data from these linkages are integrated with collected census data and used to produce estimates for dissemination as part of the standard census product line. Outputs for the census include a wide range of analysis and standard data tables, as well as custom tabulations. Only aggregate statistical estimates and analyses conforming to the confidentiality provisions of the Statistics Act and any applicable requirements of the Privacy Act are released outside of Statistics Canada.

Linkage of emergency and recovery programs and other administrative files with individual and family characteristics from the 2016 Census and selected household surveys (008-2021)

Purpose: This linkage project will help to measure the extent of income support provided during the pandemic. This project will benefit all Canadians on various levels.

Canadians will be better informed to discuss the context surrounding the measures. Furthermore, it will inform discussions about diversity and equity. In addition, it will provide relevant information to the academic community and policy-makers to better serve Canadians.

It will be possible to obtain the level of participation in the programs compared with all workers in the previous year. The integration of selected sociocultural characteristics, level of education and labour market activities that are not available in the administrative databases will enable the analysis to focus on vulnerable or discriminated populations as well as persons with a disability.

Output: To ensure compliance with the provisions of the Statistics Act and the Privacy Act, any data that will be published outside Statistics Canada and its network of Research Data Centres will first be assessed against pre-established confidentiality rules and will be censored to comply with these suppression criteria.

Once these statistical products are certified as compliant with the suppression rules, they will be verified with partner agencies and, where appropriate, published on the Statistics Canada's website.

The products will include a series of characteristic tables in spring 2021. Written analyses will follow.

Ontario Social Assistance Data Linkage Project (009-2021)

Purpose: The Ontario Ministry of Children, Community and Social Services has elaborated a research plan focusing on a better understanding of the characteristics of social assistance recipients, the recipients' interactions with the social assistance and income security systems and the impact of social assistance across a range of recipient outcomes. The project focuses in particular on the earnings, income, and health trajectories of social assistance recipients and their dependents before, during, and after their time in Ontario's caseload. As part of this project, a linkage between the Ontario Social Assistance Member Information File to multiple administrative sources held by Statistics Canada will be performed. The development of analytical research projects are also expected to help researchers, the general public and government to understand and to improve assistance policies or programs.

Output: The analysis file, once identifiers are removed, and the linkage keys will be placed in the Research Data Centre (RDC) network where deemed employees will be able to conduct specific analyses.

All access to the linked microdata file will be restricted to Statistics Canada personnel (including Statistics Canada deemed employees) whose work activities require access. Research reports and presentations to various groups will be generated from the analysis files. Only non-confidential aggregate data or tables conforming to the confidentiality provisions of the Statistics Act and any applicable requirements of the Privacy Act will be released outside of Statistics Canada.

The impact of preterm birth on socioeconomic and educational outcomes of children and families (010-2021)

Purpose: To account for the complex nature of the data and outcomes, we will employ longitudinal methods, multistate models and parametric survival models. We will answer the following questions:

What is the impact of preterm birth on short-term outcomes such as family income, maternal labor market participation, and maternal educational attainment?
What is the impact of preterm birth on long-term outcomes such as the preterm-birth survivor's educational attainment and income?

Output: Only aggregate data that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. Analytical datasets will be placed in the Research Data Centres (RDCs) and access will be granted following the standard RDC approval process. The source datasets will be anonymized and will respect variable restrictions in effect for the source datasets (e.g., hospital, vital statistics, and tax files). Major findings will be used to create research papers for publication in peer-reviewed journals and presentations at workshops and conferences.

Addition of the Diversity and Skills Database (DSD) to the Linkable File Environment (LFE) of Statistics Canada (012-2021)

Purpose: The purpose of the project is to better understand the ownership and employee characteristics of Canadian enterprises, particularly those supported by the federal government. In the initial usage of this linkage, to be conducted by Statistics Canada's Economic Analysis Division in conjunction with the Treasury Board Secretariat (TBS) of Canada at Statistics Canada's Business Data Access Centre, ownership and employee characteristics of government-supported enterprises in the Business Innovation and Growth Support (BIGS) program will be analysed. This will allow TBS and federal policy makers to determine if the demographic distribution of federal business funding is equitable, reasonable and fair, and how it should be adjusted to maximize the common good of all sectors of Canadian society.

Output: Only non-confidential aggregate statistical outputs and analysis that conform to the confidentiality provisions of the Statistics Act will be released outside Statistics Canada.

These outputs will include aggregate statistical tabulations showing diversity and skills characteristics of owners and employees of enterprises in government support programs such as those included in the Business Innovation and Growth Support program conducted by Statistics Canada on behalf of TBS. The characteristics currently in the DSD are gender, age, immigration status, and business experience.

Canadian Veteran Population Frame (013-2021)

Purpose: The purpose of this project is to establish, for the first time, a longitudinal population frame file that captures all Veterans who have served in the Canadian Armed Forces. This information will be used to expand the research and analysis on the socio-economic status of the entire Veteran population and their families.

Output: Only non-confidential data and analytical products, conforming to the confidentiality provisions of the Statistics Act and any applicable requirements of the Privacy Act will be released outside of Statistics Canada.

Alberta Interprovincial Talent Mobility (015-2021)

Purpose: The Alberta Interprovincial Talent Mobility project objective is to understand the current landscape of talent supply and retention in Alberta. In particular, the project will help quantify the talent exodus, if any, from Alberta and help inform interventions that are targeted towards retaining talented high school graduates in the Alberta post-secondary education system and the labour force. It will also inform the adequacy of current post-secondary education programming available to Albertans.

Output: The linked outcome file, with all identifiers removed, will be made available to the Alberta Ministry of Advanced Education in the Statistics Canada, Alberta Secure room, located in the Alberta Office of Statistics and information (OSI).

Linkage of APEX-AMI clinical cohort to hospitalization and socioeconomic data (016-2021)

Purpose: The purpose of this project is to create a series of outcome files resulting from the APEX-AMI files being linked to DAD, CVSD, and T1FF data. The specific aims of this project are to study the:

Differences in characteristics of patients from Canada enrolled in a clinical trial known as the Assessment of Pexelizumab in Acute Myocardial Infarction (APEX AMI) and not enrolled in the trial during the same time period (e.g. age, sex, urban/rural residence, marital status, socio-economic status (SES));
Differences in health care resource (e.g. number of hospitalizations, days in hospital, cardiovascular procedures) and long-term mortality among patients enrolled in the trial compared to those not enrolled in the trial;
Impact of marital status on long-term mortality in patients with a ST-Elevation Myocardial Infarction (STEMI); and
Impact of SES on long-term mortality in patients with a STEMI.

The integrated dataset will fill an existing data gap by examining enrollment in clinical trials through an equity, diversity, and inclusiveness (EDI) lens. For example, if we find the ratio of men to women enrolled in the trial is significantly different from the proportion of men to women who could have been enrolled in the trial, it would inform the design and conduct of future clinical trials. The integrated data will also be able to shed light on the long-term health outcomes of patients enrolled in the trial and compare them to those who were not enrolled in the trial. The linkage will allow for the examination of how social determinants of health (such as urban/rural residence, marital status, and socio-economic status) which were not captured as part of the trial, affect long-term outcomes in patients hospitalized with a STEMI.

Output:Only aggregate data that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. Analytical datasets will be placed in the Research Data Centres (RDCs) and access will be granted following the Microdata Access Portal application process. Patient identifiers resulting from the linkage will be removed from the linked datasets and the datasets will respect variable restrictions in effect for the source datasets (e.g. Discharge Abstract Database, Vital Statistics – Death Database, and T1 Family File). All linked datasets that will be produced will have their identifiers removed before they are placed in the RDCs. Major findings will be used to create research papers for publication in peer-reviewed journals and presentations at workshops and conferences.

The Impact of Surgery on Work and Earnings for those with Degenerative Conditions of the Spine, Hip and Knee (017-2021)

Purpose: The specific aim of this project is to study the impact of surgery on employment and earnings for patients with osteoarthritis of the spine, hip and knee.

Our central hypothesis is that surgical intervention for end-stage osteoarthritis of the spine, hip and knee will result in elevated workforce participation and increased earnings. We will evaluate this using linked longitudinal health and earnings data. Healthcare data will be derived from the Canadian Institute for Health Information Discharge Abstract Database (DAD), the National Ambulatory Care Reporting System (NACRS), and the Canadian Community Health Survey (CCHS). Earnings data will be obtained from the T1 Family File, which contains yearly tax returns for all Canadians.

Output:Only aggregate data that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. Analytical datasets will be placed in the Research Data Centres (RDCs) and access will be granted following the standard RDC approval process. The source datasets will be anonymized and will respect variable restrictions in effect for the source datasets (e.g., hospital, vital statistics, and tax files). All linked file(s) that will be produced will have their identifiers removed before they are placed in the RDC. Major findings will be used to create research papers for publication in peer-reviewed journals and presentations at workshops and conferences.

Atlantic Canada Opportunities Agency (ACOA), on behalf of the Atlantic Trade and Investment Growth Strategy (ATIGS) Management Committee– Data for Performance Measurement Framework (018-2021)

Purpose: The goal of the project is to provide ACOA, on behalf of the ATIGS partners (Provinces of New Brunswick, Nova Scotia, Newfoundland and Labrador, and Prince Edward Island), with statistics to assess the effectiveness of the ATIGS programs and activities. These statistics/indicators will be used to establish baselines for comparison and for target setting in their ATIGS Performance Measurement Strategy. The ATIGS' ultimate objectives are to increase export activities and foreign direct investment in Atlantic Canada.

To develop these statistics, a list of ATIGS-assisted businesses will be linked to the Business Register, the National Accounts Longitudinal Microdata File and the Trade in Exporter Characteristics. The resulting linked data will be used to produce tabulations on businesses assisted and not-assisted by ATIGS.

Output:Non-confidential aggregate statistics on businesses assisted and not-assisted by ATIGS, including, the number of exporters, the value of export sales and the number of companies exporting to more than one global market by industry, province and revenue size of firm.

Atlantic Student Tracking System (ASTS) project (019-2021)

Purpose: The objective of the Atlantic Student Tracking System project is to understand the pathways of current and prospective students in the Atlantic provinces, from Kindergarten to Grade 12 through to postsecondary education.

In particular, the project will provide policy-relevant statistical information by identifying the pathways Atlantic K-12 students follow as they enter, move through and complete their postsecondary education as well as to the labour market. The project builds upon what is currently available in the Atlantic provinces by including postsecondary and apprenticeship enrolment of students in all Canadian provinces, so that movement of high school graduates outside the Atlantic provinces can be fully understood. It also allows study of graduate outcomes related to earnings and employment.

Output:The regional linked outcome file, with all identifiers removed, will be made available to the clients in the New Brunswick University Research Data Centre.

Graduate Outcome Indicators, Project (020-2021)

Purpose: The Graduate Outcome Indicators aims to provide policy-relevant statistical aggregates on students and graduates of Alberta's universities and colleges.

In particular, the project will focus on the outcomes and pathways of students and graduates.

The expected result is that Alberta will have a greater understanding of student pathways, transitions to the labour market and outcomes over time.

Output:The linked outcome file, with all identifiers removed, will be made available to the Alberta Ministry of Advanced Education in the Statistics Canada, Alberta Secure room, located in the Alberta Office of Statistics and information (OSI).

Mitacs Economic Impact Study: Measuring Mitacs' Impact on Partner Performance (022-2021)

Purpose: The goal of the project is to estimate the effects of Mitacs' major programs on partner organizations' business performance and innovation outcomes, by identifying differences between Mitacs partners and comparable non-partner organizations. The findings will enhance Mitacs' understanding of the effectiveness of their services on the growth and innovation of its partners.

To undertake the project, a list of Mitacs partners will be linked to the Business Register and the National Accounts Longitudinal Microdata File. The resulting linked data will be used to compare the performance of Mitacs partners to a similar sample of firms that have not received Mitacs support.

Output:Statistics Canada will provide the following output to Mitacs:

1. A linkage report showing the percentage of Mitacs partners matched with the Business Register and the National Accounts Longitudinal Microdata File;

2. A document containing non-confidential tabulations based on the estimation results (i.e., from comparing the outcomes of Mitacs partners to non-partners); and

3. A methodology note describing the methods adopted, the stages of the analysis and the limitations of the study.

Only non-confidential aggregate statistical outputs and analyses that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada

Developing a Socio-Demographic Profile of Recipients of the Wage Earner Protection Program to Support Program Evaluation (023-2021)

Purpose: The main objective of this study is to develop a profile of key socio-demographic characteristics for recipients of the Wage Earner Protection Program (WEPP). The linkage will provide information about income, employment, disability and ethnicity. The socio-demographic profile will be used to evaluate the demographics of individuals benefitting from the Wage Earner Protection Program in order to inform future policy decisions. The evaluation will be presented to ESDC's Performance Measurement and Evaluation Committee in 2022. Based on the analysis of the linked files, observations about the program will be made that could result in changes to how the program operates.

Output: All access to the linked microdata file will be restricted to Statistics Canada personnel (including Statistics Canada deemed employees) whose work activities require access. Only aggregate data that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. The linked outcome files will be made available in Statistics Canada's Research Data Centre. Findings will be used in research papers and in presentations at workshops and conferences. Statistics Canada will also explore opportunities to collaborate with the client, as well as other partners, on data releases on this topic.

Evaluation of Federally-Funded Drug Treatment Courts (2015-2018 Cohort) (024-2021)

Purpose: Drug Treatment Courts (DTCs) are specialized problem-solving courts that provide individuals involved in non-violent crime related to substance use with an alternative to the conventional justice system by offering them the opportunity to complete a judicially-supervised substance use treatment program. The objective of this study is to estimate the extent to which federally funded DTCs are associated with reductions in re-contact with the criminal justice system compared to the conventional criminal justice process. The results will inform future criminal justice policy and program decisions aimed at improving public safety.

Output:Only non-confidential aggregate statistics and analyses that will not result in the identification of an individual person, business or organization will be released outside of Statistics Canada. Findings will be reported in the form of an analytical report, which may be published by the Department of Justice Canada.

Profiling Investment Readiness Program (IRP) Beneficiaries and Non-Beneficiaries (026-2021)

Purpose: The purpose of the project is to better understand the financial and other characteristics of IRP applicants and beneficiaries that are representative of the social purpose organizations that Employment and Skills Development Canada (ESDC) is broadly targeting for financial support in capacity-building activities that enable them to access the social finance market. The project will also enable ESDC and the third parties administering program funding to refine the criteria for the selection of beneficiaries and to evaluate the impact of the program on different types of beneficiaries.

Output:Only non-confidential aggregate statistical outputs and analysis that conform to the confidentiality provisions of the Statistics Act will be released outside Statistics Canada. The output will be custom designed tables and analysis of sources of funding, organizational capacity, as well as diversity and inclusion prior to applying to the IRP and, to the extent possible, during and after applying to the IRP funding. Indicators of change in performance over a three year period will be developed, along with estimates based on other data available in the Linkable File Environment (LFE) such as location, size, status, revenue, employment and diversity, among others.

A profile of the Canadian quantum sector (028-2021)

Purpose: The goal of this project is to produce the first profile of the quantum computing sector in Canada. This first profile will serve as a baseline to assess the impact of the Government of Canada's National Quantum Strategy.

A list of businesses in the quantum sector in 2021 from Innovation, Science and Economic Development Canada will be linked to the Canadian Employer–Employee Dynamics Database to create a profile of the sector, specifically, on aspects pertaining to the business, such as revenue and employment, and on aspects of the workers, such as gender and age.

Output: Statistics Canada will provide the following output to Innovation, Science and Economic Development Canada:
1. A methodology report explaining the file matching processes, constraints and key issues related to the quality of the data;
2. A document containing non-confidential statistics for the quantum sector, such as: the total revenue; sales; net income; average number of years in business; total employment; as well as the number of workers by sex, age, income-level and geography.

Only non-confidential aggregate statistical outputs and analyses that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada

Improving residence information on Canadian Vital Statistics – Deaths Database (029-2021)

Purpose: The specific near-term aim of this project is to address the gaps in the understanding of COVID-19 mortality related to the characteristics of the decedent's residence and, in particular, better identify deaths occurring to residents of nursing and residential care facilities in the COVID-19 pandemic.

This will be performed by linking the decedent in the Canadian Vital Statistics – Deaths (CVSD) database to the Address Register (AR)/Statistical Building Register (SBgR), Business Register (BR), Canadian Housing Statistics Program (CHSP) data, and Nursing and Residential Care Facilities Survey (NRCFS) through the decedent's address of residence.

The demand for such information is high and the Public Health Agency of Canada (PHAC) and other stakeholders have explicitly communicated this data need to Statistics Canada to help support their responses to the pandemic.

Additionally, in the longer term, the purpose of the linkage is to fill data gaps and improve knowledge related to:

The influence of collective or structural characteristics of the dwelling on broader mortality outcomes.
The influence of neighbourhood characteristics on mortality outcomes.

Output:

A derived categorical variable that describes, at a high level, the characteristics of the dwelling of the decedent will be added to the master file of the Canadian Vital Statistics – Deaths database.
Non-confidential aggregate statistics and analyses that conform to the confidentiality provisions of the Statistics Act intended for release outside of Statistics Canada.

Analytical datasets may also be placed in the Research Data Centres (RDCs) and access will be granted following the standard RDC approval process. The source datasets will be anonymized and will respect variable restrictions in effect for the source datasets (e.g., vital statistics).

Post-restructuring performance of firms (030-2021)

Purpose: This project will enable an analysis of the population of firms that file and complete an insolvency proposal, allowing for a thorough assessment on the degree to which non-viable firms are being restructured in Canada. It relies on the linkage of business insolvency data from the Office of the Superintendent of Bankruptcy to the Business Register and the National Accounts Longitudinal Microdata File to track businesses at different stages of the insolvency process. Using business indicators derived from the linked data, such as industry, firm size and firm age, it will help to identify what factors drive insolvency and the post-restructuring performance.

Linkage of Canadian Disability Savings Programs (CDSP) admin data to the Canadian Survey on Disability (CSD) (031-2021)

Purpose: The purposes of this data linkage is multi-fold:

Provide the Canadian public with greater insight to better inform on the social and economic conditions of persons with disabilities. In particular, the additional data contained In the CDSP dataset will improve insight with regards to usage of some of Canada's key policies targeting persons with disabilities, in particular, allowing research on intersectionalities of Canadians who use the CDSP programs.
By working collaboratively with stakeholders to achieve and disseminate this new linked data, the final result will support and improve insight and decision-making by encouraging and facilitating more in depth policy analysis with regards to persons with disabilities and the Canadian Disability Savings Program.

In this context, a merge between the Canadian Survey on Disability and the Canadian Disability Savings Program represents a good strategy to learn more and make information available to the public.

Output: The output from the linkage will be a non-confidential microdata file (unique identifiers removed), and will be made available to Statistics Canada deemed employees following the standard approval process via Statistics Canada's, Research Data Centre's and Federal Research Data Centre. All analyses performed on the file will be assessed to ensure that they conform to the confidentiality provisions of the Statistics Act.

A Comprehensive Analysis of the Pathways to Education Program on Health and Crime Outcomes of Eligible Participants (033-2021)

Purpose: The study will examine the average outcomes of the Pathways to Education Canada (Pathways) program on its participants. It builds upon the previous studies focusing on the economic and academic outcomes of Pathways, and extends to other non-pecuniary outcomes, such as health and crime. Specifically, it will examine the channels through which Pathways improves the health and mitigates crime outcomes of its participants. This study will contribute to the academic literature on identifying the channels through which comprehensive interventions delivered at the high school level improve outcomes. The findings from the study will be used by ESDC to more accurately evaluate the Pathways program. More generally, they will enable the Department to better design and deliver the program in helping students in disadvantaged communities in Canada. In addition, the project will contribute to building the Department's capacity – as part of the departmental evaluation plan in 2022 – monitoring and evaluating early intervention and social partnership initiatives.

Output:Only non-confidential aggregate statistical outputs and analyses that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. The information will be presented in the form of tables of regression results and summary statistics related to the project's goal of evaluating the Pathways program. Access to the analytical file by researchers who have become deemed employees of Statistics Canada, will be by following the approved standard procedures for access via Statistics Canada's Federal Research Data Centre or Research Data Centre.

The performance of businesses supported by the Atlantic Fisheries Fund (034-2021)

Purpose: The goal of the project is to provide Fisheries and Oceans Canada (DFO) with official statistics for pan-Atlantic performance and individual provinces to assess the effectiveness of the Atlantic Fisheries Fund (AFF), an economic development program for the seafood sector in Atlantic Canada. The AFF seeks to transform and drive innovation in the Atlantic fish and seafood sector with the objective of realizing sustainable economic growth in the sector.

To develop these statistics, a list of AFF-assisted businesses will be linked to the Business Register and the National Accounts Longitudinal Microdata File. The resulting linked data will be used to produce tabulations on businesses assisted and not-assisted by the AFF.

Output: Non-confidential aggregate statistics on businesses assisted and not-assisted by the AFF, including, number of businesses, employment, gross profit, cost of goods sold and financial ratios.

Coverage of vulnerable populations in different statistical programs: an assessment of Canadian death records, the Census of Population and administrative data (035-2021)

Purpose: The linked data analyzed in this study will be used to estimate whether persons in the death records are absent from administrative datasets or the Census of Canada in the seven years preceding death. With this information, it will be possible to assess the population that "falls out" of the tax filing, foregoing government benefits that they may have used to improve their situation. It will also be possible to see persons who, before death, do not participate in civic activities, such as the census. Together these results will respond to a data gap by providing information that can be used as insight into better ways of delivering government benefits and better methods of assessments of the populations at risk of social exclusion.

Output: Only non-confidential statistical aggregates, which confirm to the confidentiality provisions of the Statistics Act, will be released outside of Statistics Canada.

All products containing analytical text or data tabulations based on linked data will be disseminated in accordance with Statistics Canada's policies, guidelines and standards. Outputs from this linkage will include a range of analysis and data tables, as well as custom tabulations.

Linkage of the 2020 General Social Survey (cycle 35), T1FF, Emergency and Recovery Benefits (ERB) file, and Longitudinal Immigrant Database (IMDB) (037-2021)

Purpose: This integrated analytical dataset will allow researchers to provide new insights into the impacts of the pandemic on diverse population groups. The linked dataset will be used to examine the role government transfer payments play in reducing inequality and the societal impacts of long-term economic exclusion (e.g., lack of social cohesion).

Output: The integrated data, which will not contain any direct personal identifiers, will be available to deemed employees to use in a Research Data Centre (RDC). Access will be granted following the standard RDC process. All data and analytical products to be released outside of Statistics Canada will conform to the confidentiality provisions of the Statistics Act.

Linkage of the Canadian Correctional Services Survey to the Census of Population and the National Household Survey for Disaggregated Data Evaluation (038-2021)

Purpose: The Canadian Correctional Service Survey (CCSS) collects comprehensive microdata from correctional service programs in Canada, including whether persons supervised self-report as Indigenous or to a racialized group. Over-representation of Indigenous persons and other racialized groups, in particular Black Canadians, is one of the most important issues facing the criminal justice system. To better understand Indigenous and Racialized group information being collected by correctional service programs, and whether or not there may be under-reporting in the correctional data, CCJCSS proposes a record linkage between the CCSS and the Census of Population. The project will identify individuals responding to both the corrections survey and the Census, to compare how consistently Indigenous and racialized group information is being reported overall between the two data collection mechanisms.

Output: Only non-confidential aggregated tables, conforming to the confidentiality provisions of the Statistics Act, will be released outside of Statistics Canada. Confidentiality rules for the Census would be applied to all products before release.

Linkage of the Canadian Correctional Services Survey to the Census of Population and the National Household Survey for Disaggregated Data Evaluation (038-2021)

Addition of the Canadian Survey of Cyber Security and Cybercrime (CSCSC) to the Linkable File Environment (LFE) of Statistics Canada (040-2021)

Purpose: The proposed activity would link the enterprises in the Linkable File Environment (LFE) of the Centre for Special Business Projects (CSBP) to the Canadian Survey of Cyber Security and Cybercrime (CSCSC) of Investment, Science and Technology Division (ISTD).

The initial usage of the linkage of CSCSC and LFE is a project between Investment, Science and Technology Division (ISTD), Innovation, Science and Economic Development Canada (ISED) and Public Safety Canada (PS) to address data gaps related to digital economy statistics by leveraging existing data holdings at Statistics Canada. One area that ISTD, ISED and PS have identified as a data gap is the lack of a granular understanding of the determinants of usage of digital technologies by enterprises, particularly technologies related to data protection and cyber security. In order to address that data gap, the requested linkage will help to obtain characteristics of enterprises which are suspected to be related to technology adoption.

Output: Only non-confidential aggregate statistical outputs and analysis that conform to the confidentiality provisions of the Statistics Act will be released outside Statistics Canada. The linked analysis file will made available for access by Statistics Canada deemed employees via the standard approved process of Statistics Canada’s Business Data Access Centre.

These outputs will include data tables which provide more detailed descriptive statistics regarding the types of enterprises participating in the digital economy, and potentially data models to better understand all the determinants of adoption of digital technologies. ISED and PS will ultimately utilize these data products to build more tailored policies, programs and tools to help Canadian enterprises improve their cyber security resilience and grow Canada’s digital economy.

Canadian Economic News, May 2021 edition

This module provides a concise summary of selected Canadian economic events, as well as international and financial market developments by calendar month. It is intended to provide contextual information only to support users of the economic data published by Statistics Canada. In identifying major events or developments, Statistics Canada is not suggesting that these have a material impact on the published economic data in a particular reference month.

All information presented here is obtained from publicly available news and information sources, and does not reflect any protected information provided to Statistics Canada by survey respondents.

COVID-19 timeline

On May 6th, the Government of the Northwest Territories announced it had extended the State of Emergency in the City of Yellowknife until May 20th. On May 20th, the Government extended the State of Emergency until June 3rd.
On May 11th, the Government of the Northwest Territories announced it had extended the territory-wide Public Health Emergency until May 25th. On May 25th, the Government extended the Public Health Emergency until June 8th.
On May 11th, the Government of British Columbia announced it had formally extended the provincial state of emergency until May 25th. On May 25th, the Government extended the state of emergency until June 8th.
On May 14th, the Government if Nova Scotia announced it was renewing the state of emergency, effective May 16th, until May 30th. On May 28th, the Government renewed the state of emergency until June 13th.
On May 27th, the Government of Nunavut announced it had extended the territory's public health emergency until June 10th.
On May 27th, the Government of the Yukon announced it was extending the State of Emergency for up to 90 days.
On May 28th, the Government of Manitoba announced it was further extending the state of emergency for a period of 30 days.

Selected COVID-19 responses

The Government of the Northwest Territories announced on May 3rd that due to a recent outbreak at a school, new measures would be introduced, including:
- Closing all schools in Yellowknife, Dettah, Ndilǫ̨ and Behchokǫ̀ to in-class learning until further notice;
- Suspending all extracurricular, club, and sports activities for kids under the age of 18; and
- Recommending non-essential travel in and out of Yellowknife be cancelled or deferred at this time.
The Government said all daycare and day homes are able to stay open.
On May 12th, the Government announced it was removing the temporary COVID-19 restrictions put in place for school closures in Yellowknife, Ndilǫ̨, Dettah, and Behchokǫ̀ effective May 17th.
The Government of Nunavut announced on May 3rd it had suspended Nunavut's Common Travel Area with the Northwest Territories (NWT), effective immediately, and that anyone travelling to Nunavut from the NWT must isolate in Yellowknife for 14 days before returning into the territory.
The Government of Alberta announced on May 4th that effective May 5th the following mandatory health measures would apply to all communities with more than 50 cases per 100,000 people and with 30 or more active cases:
- All outside social gatherings must be limited to no more than five people, a decrease from the previous 10-person limit;
- All indoor social gatherings are still prohibited;
- All indoor fitness must close;
- No more than 10 people can attend funeral services, a decrease from the current limit of 20 people;
- Retail services must limit customer capacity to 10%;
- All post-secondary learning must shift to online learning only;
- Working from home remains mandatory; and
- Any workplace with transmission of three or more cases will be required by health officials to close for 10 days.
Effective May 7th:
- All kindergarten to Grade 12 students will temporarily shift to at-home learning.
Effective May 9th:
- In-person dining on patios is prohibited;
- Hair salons, barbers, nail salons, estheticians, tattoos and piercing, must close;
- All outdoor sports and recreation are now prohibited except with members of your household;
- All indoor sport and recreation is prohibited; and
- All indoor performance activity is prohibited.
On May 19th, the Government announced that kindergarten to Grade 12 students would return to classrooms in all regions except for the Regional Municipality of Wood Buffalo.
On May 26th, the Government released its Open for Summer Plan, a three-stage road map to lifting health restrictions based on vaccination rates and COVID-19 hospitalizations. The Government said the province would enter Stage 1 on June 1st.
The Government of Quebec announced on May 4th the end of special emergency measures and the application of the maximum alert level (red) measures for the Capitale-Nationale, Chaudière-Appalaches, and the Outaouais regions, and that:
- High school students will go back to school;
- The curfew will begin at 9:30 p.m. rather the current 8:00 p.m. start; and
- Non-essential businesses will be able to reopen.
On May 8th, the Government announced it would move the Estrie region to the maximum alert level (red) effective May 10th and that measures would include:
- The closure of restaurants, except for delivery and take-out;
- A limit of 25 people in places of worship;
- Outdoor sports or leisure activities permitted only with people residing at the same address or by a group of 8 people with distancing;
- The closure of gyms; and
- Indoor sports and leisure activities are permitted with occupants of the same private residence including swimming pools, skating rinks and places for playing tennis and badminton.
The Government said primary and secondary schools will remain open.
On May 11th, the Government announced that effective May 17th, special emergency measures in the city of Gatineau and in the Les Collines-de-l'Outaouais and Pontiac RCMs would end.
On May 19th, the Government announced that the special emergency measures in effect in the MRC du Granit (Estrie region), MRC des Etchemins, Beauce-Sartigan and Robert-Cliche (Chaudière-Appalaches region), and the MRCs of Kamouraska, Témiscouata, Rivière-du-Loup and Les Basques (Bas-Saint-Laurent region) may be lifted effective May 24th. The Government also said that effective May 28th, the following restrictions will take effect in all regions of Quebec:
- The curfew will be lifted;
- Outdoor private gatherings will be permitted on private grounds with a maximum of 8 people;
- Outdoor terraces of restaurants will open to customers;
- Travel between regions will be permitted; and
- Large rooms and outdoor stadiums will be able to accommodate a maximum of 2,500 people.
On May 25th, the Government announced that the regions of the Capitale-Nationale, Laurentides, Lanaudière, Montérégie, Outaouais, Bas-Saint-Laurent, Chaudière-Appalaches, and Estrie would move from the maximum alert level (red) to the orange level and that the following measures would now apply:
- The reopening of restaurants, with restrictions;
- The return to full-time class for students in 3rd, 4th, and 5th secondary;
- A maximum of 100 people in places of worship.
The Government of Canada announced on May 5th it authorized the use of the Pfizer-BioNTech COVID-19 vaccine in children 12 to 15 years of age. On May 20th, the Government announced it was extending travel restrictions on non-essential international travel and non-essential travel with the United States until June 21st. On May 21st, the Government announced it was extending the suspension of all direct flights from India and Pakistan into Canada until June 21st.
The Government of Nova Scotia announced further restrictions on May 7th and that effective May 8th:
- Nova Scotians will have to designate one shopper per household and retail stores that offer in-person shopping will impose a limit of one shopper per household; and
- Retail stores that primarily offer products and services that are essential to the life, health or personal safety of people and animals can continue to provide limited in-person service only to a maximum of 25% of the store capacity.
The Government also said that new border measures would take effect on May 10th, including:
- Nova Scotia's border will close to people intending to move here; and
- The border will close to people coming from Prince Edward Island and Newfoundland and Labrador.
On May 10th, the Government announced new border measures took effect and that only permanent residents of Nova Scotia and people travelling for essential reasons can enter the province.
On May 19th, the Government announced that current public health restrictions will remain in place across Nova Scotia until at least the second week of June and that public and private schools will continue at-home learning for the remainder of the school year.
On May 28th, the Government announced it will gradually reopen under a five-phase plan based on COVID-19 activity, public health and testing capacity, hospitalizations, and vaccination rates. The Government said restrictions would be easing effective June 2nd. The Government also said that in-person classes would resume on June 2nd at all Nova Scotia public and private schools outside of Halifax Regional Municipality and Sydney.
The Government on Manitoba announced on May 7th that the following additional public health order restrictions would be in effect from May 9th until May 30th:
- Outdoor gatherings in public places that include people from multiple households are limited to a maximum of five people;
- Restaurants, bars and patios will close to in-person dining but can still provide take-out and delivery services;
- Gyms and fitness centres will close;
- Casinos remain closed and VLTs will close;
- Museums, galleries and libraries will close;
- Indoor community, cultural, and religious gatherings are prohibited;
- Personal services such as estheticians, barbers, salons, and tanning salons will close;
- Indoor sports and recreation, including after-school activities, will close;
- Outdoor sports and recreation activities will have a maximum of five participants and organized team games will not be permitted;
- Dance, theatre, and music schools will close;
- Day camps will close; and
- Retail stores, markets, and garden centres will be able to open at 10% capacity and malls will be open to a maximum of 10% of the facility's capacity.
On May 9th, the Government announced that all kindergarten to Grade 12 schools in the City of Winnipeg and the City of Brandon will move to remote learning effective May 12th until May 30th.
On May 20th, the Government announced that the following additional restrictions would be in effect from May 22nd until May 26th:
- Outdoor gatherings with anyone from outside a household are no longer allowed and this applies to all recreation spaces including playgrounds, golf courses, parks, and sports fields; and
- Only one person per household will be allowed to enter a business.
On May 25th, the Government announced that the current public health orders that were put in place for the May long weekend would remain in effect until May 29th and include:
- Indoor public gatherings are not permitted and visitors are not permitted on private property;
- Outdoor gatherings with anyone from outside a household are not allowed and this applies to all recreation spaces including playgrounds, golf courses, parks, and sports fields;
- Retail businesses may only operate at 10% and only one person per household will be allowed to enter a business; and
- Many businesses and organizations will remain closed for in person service including gyms and fitness clubs, restaurants and bars, personal service businesses, museums, galleries, and libraries.
On May 27th, the Government announced the following public health orders would be put in place effective May 29th for the next two weeks:
- Indoor public gatherings are not permitted;
- Requirements for employers to allow employees to work from home as much as possible;
- Outdoor gatherings with anyone from outside a household are not permitted;
- Retail businesses may only operate at 10% capacity and only one person per household will be allowed to enter a business;
- Increased requirements for malls to manage capacity and access to eliminate gatherings and ensure compliance with shopping; and
- Many businesses and organizations will remain closed for in-person service, including gyms and fitness clubs, restaurants and bars, personal service businesses, museums, galleries, and libraries.
The Government also said that Kindergarten to Grade 12 schools currently learning remotely in the cities of Winnipeg and Brandon, and in the Red River Valley and Garden Valley school divisions, will continue until June 7th. Schools in Dauphin will continue remote learning until June 9th.
The Government of Saskatchewan announced on May 9th it had set May 30th as the target date for the commencement of Step One of the Re-Opening Roadmap, and that at that time the following changes would be made:
- Restaurants and bars open with restrictions;
- 30% capacity at places of worship;
- Group fitness classes involving intense training, like aerobics and spin, can resume; and
- Competition and game play for outdoor team sports can proceed.
On May 16th, the Government announced that effective May 17th, all Regina restaurants and licensed establishments would be able to resume in-person dining according to the guidance currently applicable province-wide.
On May 24th, the Government announced that the province had reached the Step Two threshold on the province's Re-Opening Roadmap and that effective June 20th Step Two would begin.
On May 13th, the Government of Ontario announced it had extended the Stay-at-Home Order until at least June 2nd and that all public health and workplace safety measures under the provincewide emergency brake would also remain in effect. On May 20th, the Government released its Roadmap to Reopen, a three-step plan to reopen the province and lift public health measures. The Government said it expects to enter Step One of the Roadmap the week of June 14th and that the provincewide emergency brake restrictions remain in effect while the province assesses when it will be moving to Step One.
The Government of Yukon on May 21st announced it would begin lifting public health restrictions on May 25th, including:
- Fully vaccinated people will no longer need to self-isolate upon entry to the territory;
- Bars and restaurants will be able to return to full capacity for table service;
- Social bubbles can increase to 20 individuals;
- Social gathering sizes can increase, with indoor gatherings rising to 20 individuals and outdoor gatherings up to 100 individuals;
- Organized indoor and outdoor gatherings and events can increase to 200;
- Funerals, weddings, and faith-based services can increase to 200 individuals;
- Gyms and recreation centres can increase to 200 individuals; and
- Camps and recreational programs can increase to 20 individuals indoors and 100 individuals outdoors.
The Government of Newfoundland and Labrador announced on May 24th that all communities along the Trans Canada Highway Route 1 from Gambo to Badger will move to Alert Level 4, as well as communities along the Trans Canada Highway Routes 320, 330, 340 and 350 and most of the branches of these routes. On May 30th, the Government said that communities in the St. George's – Stephenville – Port au Port area on the west side of the Trans Canada Highway would move to Alert Level 4.
The Government of British Columbia announced on May 25th that the province was moving forward with the first step of a four-step plan to restart and that the following restrictions would apply immediately:
- Maximum of five visitors or one household allowed for indoor personal gatherings;
- Maximum of 10 people for outdoor personal gatherings;
- Maximum of 10 people for seated indoor organized gatherings;
- Maximum of 50 people for seated outdoor organized gatherings;
- Recreational travel only within travel region (travel restrictions extended);
- Indoor and outdoor dining for up to six people;
- Resume outdoor sports (games) with no spectators, low-intensity fitness;
- Start gradual return to workplaces; and
- Return of indoor in-person faith-based gatherings with reduced capacity.
The Government of Prince Edward Island on May 27th released its Moving Forward plan, a five-step approach to relaxing COVID-19 public health measures based on vaccine rates, disease transmission, outbreak risks, and health care system and public health capacity. The Government said Step 1 was projected for June 6th.
The Government of New Brunswick on May 27th announced guidelines outlining the path toward the Green level of the COVID-19 recovery plan, a three-phase approach to loosen restrictions, with target dates based on anticipated vaccination rates and low numbers of COVID-19 hospitalizations. The Government said the first phase is expected to come into effect on June 7th.

Resources

The Government of Canada announced it had approved the NOVA Gas Transmission Ltd. (NGTL) North Corridor System Expansion Project and that the proponent must comply with 37 binding conditions related to safety, environmental and wildlife protection, Indigenous engagement, and protection of Indigenous rights and interests.

Manufacturing

Oshawa-based General Motors of Canada announced it is accelerating the start of production of full-size trucks at Oshawa Assembly to the fourth quarter of this year, ahead of the previous target of January 2022. The company said the $1.3 billion investment is helping to create nearly 1,700 new jobs and indirect supplier jobs.
British Columbia-based Paper Excellence and Domtar Corporation of South Carolina announced they had entered into a strategic business combination under which the Paper Excellence group of companies will acquire all of the issued and outstanding shares of Domtar common stock for an enterprise value of approximately USD $3.0 billion. The companies said the transaction is expected to close in the second half of 2021, subject to regulatory and Domtar shareholder approval and other customary closing conditions.

Transportation

Burlington, Ontario-based Greyhound Canada announced it had discontinued all operations on its remaining routes in Ontario and Quebec and will permanently close all services in Canada effective May 13th.
Toronto-based Porter Airlines Inc. announced it was resetting its tentative date for resuming flights to July 20th.
Montreal-based Air Transat announced that, due to continued travel restrictions both in Canada and in the destinations it serves, its operations are temporarily suspended until July 29th.

Other news

The Government of Canada announced on April 30th that Bill C-29 had received Royal Assent and that the general strike at the Port of Montreal will end and all port operations must resume effective May 1st.
The Office of the Superintendent of Financial Institutions (OSFI) announced that, effective June 1, the revised calculation of the minimum qualifying rate for uninsured mortgages (i.e., residential mortgages with a down payment of 20% or more) will be the greater of the contract rate plus 2.00% or 5.25%. The Government of Canada later announced that it will align with OSFI by establishing a new minimum qualifying rate for insured mortgages, subject to review and periodic adjustment.
Quebec's minimum wage increased from $13.10 per hour to $13.50 per hour on May 1st.
Washington State-based Amazon.com, Inc. announced it was hiring 75,000 people in its fulfilment and logistics network across the United States and Canada and that hiring is now underway.

United States and other international news

The Bank of England's Monetary Policy Committee (MPC) voted to maintain the Bank Rate at 0.1%. The MPC also voted to maintain the stock of sterling non-financial investment-grade corporate bond purchases at £20 billion, and to continue with the existing programme of UK government bond purchases, maintaining the target for the stock of these government bonds at £875 billion and the total stock of asset purchases at £895 billion.
The Reserve Bank of Australia (RBA) maintained the targets for the cash rate and the yield on 3-year Australian Government bonds at 0.10%. The last change in the target for the cash rate was a 15 basis points reduction in November 2020. The RBA also maintained the parameters of the Term Funding Facility and the government bond purchase program.
The Monetary Policy and Financial Stability Committee of Norway's Norges Bank decided to keep the policy rate unchanged at 0.0%. The last change in the policy rate was a 25 basis points reduction in May 2020.
The Reserve Bank of New Zealand (RBNZ) kept the Official Cash Rate (OCR), its main policy rate, unchanged at 0.25%. The last change in the OCR was a 75 basis points reduction in March 2020. The RBNZ also kept the Large Scale Asset Purchase and the Funding for Lending programmes unchanged.
On May 8th, Georgia, U.S.-based Colonial Pipeline Company announced it had been the victim of a cybersecurity attack and, as a result, took certain systems offline to contain the threat, resulting in the temporary halting of all pipeline operations. On May 12th, the company said it had initiated the restart of pipeline operations and on May 17th, the company said it was fully operational and transporting refined products (gasoline, diesel, and jet fuel) at normal levels.
Texas-based AT&T Inc. and Discovery, Inc. of New York announced a definitive agreement to combine WarnerMedia's entertainment, sports, and news assets with Discovery's nonfiction and international entertainment and sports businesses to create a standalone global entertainment company. The companies said that under the terms of the agreement, AT&T would receive USD $43 billion and that the transaction is expected to close in mid-2022, subject to regulatory and Discovery shareholder approvals and customary closing conditions.

Financial market news

West Texas Intermediate crude oil closed at USD $66.32 per barrel on May 31st, up from a closing value of USD $63.58 at the end of April. Western Canadian Select crude oil traded in the USD $47 to $54 per barrel range throughout May. The Canadian dollar closed at 82.84 cents U.S. on May 31st, up from 81.40 cents U.S. at the end of April. The S&P/TSX composite index closed at 19,730.99 on May 31st, up from 19,108.33 at the end of April.

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Date modified:: 2025-04-10