The Chat with an expert series has been discontinued.
Statistics Canada will engage with its users via many other methods such as through its information sessions, as well as via its official social media accounts (which are listed on the Stay connected page), through its Live chat feature, or contact us.
| NAPCS-CANADA | Month | |
|---|---|---|
| 202201 | 202202 | |
| Total commodities, retail trade commissions and miscellaneous services | 0.75 | 0.73 |
| Retail Services (except commissions) [561] | 0.75 | 0.72 |
| Food at retail [56111] | 0.71 | 1.28 |
| Soft drinks and alcoholic beverages, at retail [56112] | 0.54 | 0.59 |
| Cannabis products, at retail [56113] | 0.00 | 0.00 |
| Clothing at retail [56121] | 1.61 | 2.09 |
| Footwear at retail [56122] | 1.75 | 1.79 |
| Jewellery and watches, luggage and briefcases, at retail [56123] | 5.71 | 5.55 |
| Home furniture, furnishings, housewares, appliances and electronics, at retail [56131] | 2.20 | 0.82 |
| Sporting and leisure products (except publications, audio and video recordings, and game software), at retail [56141] | 3.06 | 1.98 |
| Publications at retail [56142] | 6.03 | 6.88 |
| Audio and video recordings, and game software, at retail [56143] | 0.50 | 0.42 |
| Motor vehicles at retail [56151] | 2.80 | 2.46 |
| Recreational vehicles at retail [56152] | 7.32 | 5.07 |
| Motor vehicle parts, accessories and supplies, at retail [56153] | 2.01 | 2.17 |
| Automotive and household fuels, at retail [56161] | 1.65 | 1.39 |
| Home health products at retail [56171] | 2.40 | 2.53 |
| Infant care, personal and beauty products, at retail [56172] | 2.17 | 2.22 |
| Hardware, tools, renovation and lawn and garden products, at retail [56181] | 2.93 | 3.39 |
| Miscellaneous products at retail [56191] | 2.87 | 2.17 |
| Total retail trade commissions and miscellaneous services Footnote 1 | 2.17 | 1.81 |
Footnotes
|
||
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.
Statistics Canada conducts this survey every two years to collect detailed information on water use by manufacturing, mining, and electrical power generating industries in Canada. The survey collects information on who uses water, how much, where and at what cost. These data will be used to develop environmental accounts and indicators.
The survey will ask about the following for your plant, operation and/or facility:
Data from this survey are used by all levels of government in establishing informed environmental policies. The private sector also uses this information in the corporate decision-making process.
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.
Data are collected under the authority of the Statistics Act, Revised Statutes of Canada, 1985, Chapter S-19.
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.
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.
To reduce respondent burden, Statistics Canada has entered into data sharing agreements with provincial and territorial statistical agencies and other government organizations, which have agreed to keep the data confidential and use them only for statistical purposes. Statistics Canada will only share data from this survey with those organizations that have demonstrated a requirement to use the data.
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 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.
For this survey, there are Section 12 agreements with the statistical agencies of Prince Edward Island, the Northwest Territories and Nunavut as well as with Environment Canada.
For agreements with provincial and territorial government organizations, the shared data will be limited to information pertaining to business establishments located within the jurisdiction of the respective province or territory.
1. Please 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.
2. Please 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.
3. Please verify or provide the current operational status of the business or organization identified by the legal and operating name above.
4. Please 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
5. You indicated that is not the current main activity. Was this business or organization's main activity ever classified as: {specified activity}?
6. Please search and select the industry classification code that best corresponds to this business or organization's main activity.
Select this business or organization's activity sector (optional)
7. You have indicated that the current main activity of this business or organization is: {specified activity}. Are there any other activities that contribute significantly (at least 10%) to this business or organization's revenue?
8. Approximately what percentage of this business or organization's revenue is generated by each of the following activities?
When precise figures are not available, please provide your best estimates.
| Percentage of revenue | |
|---|---|
| Main activity | |
| Secondary activity | |
| All other activities | |
| Total percentage |
Important reminder for this questionnaire:
When asked in this questionnaire to provide information about the plant/operation/facility, please refer to the customized description of the plant location provided in the electronic questionnaire.
Reporting period:
For the purpose of this survey, all reported information should be for the calendar year from January 1, 20xx to December 31, 20xx.
Reporting instructions:
1. Was this plant/operation/facility in operation at least one day during the 20xx calendar year?
For the purpose of this survey, "in operation" includes plants/operations/facilities that are temporarily closed but there was some form of water use
e.g., water for sanitary services like toilets and janitorial services, water use for cooling, condensing and steam, process water or pollution control.
All months
2. Was the plant/operation/facility specified below located in {the specified operating province} during the 20xx calendar year? (For Fossil-Fuel and Nuclear Electric Power Generating Plants, and Mineral Extraction Industries.)
If the plant/operation/facility was situated in more than one location during 20xx, please report the province or territory for the last location of the plant/operation/facility in the 20xx calendar year.
This information is being confirmed to ensure the reported figures contribute to the correct provincial or territorial estimates.
In which province or territory was the plant/operation/facility last located?
3. Was {the specified postal code} the postal code for the location specified below during the 20xx calendar year? (For Manufacturing Industries.)
If the plant/operation/facility was situated in more than one location during 20xx, please report the postal code for the last location of the plant/operation/facility in the 20xx calendar year.
This information is being confirmed to ensure the reported figures contribute to the estimates for the correct drainage region.
What was the postal code?
Example: A9A 9A9
Postal code
4. In 20xx, what was the average number of people working on the premises of this plant/operation/facility in full-time equivalents (FTE)?
Include permanent, contract and casual employees that work on the premises.
Employment may be full-time or part-time, FTE converts part-time jobs to full-time jobs based on the hours worked. For example, if out of four employees employed at your plant/operation/facility, one works full-time and the remaining three work the equivalent of half of a full time job, then: FTE employment = 1 + ½ + ½ + ½ = 2.5.
When exact figures are not available, please provide your best estimate.
Number of people
e.g., 2.5
5. How many days did this plant/operation/facility operate in 20xx?
For the purpose of this survey, "in operation" includes plants/operations/facilities that are temporarily closed but there was some form of water use
e.g., water for sanitary services like toilets and janitorial services, water use for cooling, condensing and steam, process water or pollution control.
For the purpose of this survey, "days" refers to calendar days.
When exact figures are not available, please provide your best estimate.
Days
6. How many weeks did this plant/operation/facility operate in 20xx?
For the purpose of this survey, "in operation" includes plants/operations/facilities that are temporarily closed but there was some form of water use
e.g., water for sanitary services like toilets and janitorial services, water use for cooling, condensing and steam, process water or pollution control.
When exact figures are not available, please provide your best estimate.
Weeks
7. On average, how many days per week did this plant/operation/facility operate in 20xx?
For the purpose of this survey, "days" refers to calendar days.
When exact figures are not available, please provide your best estimate.
Days per week
8. On average, how many hours did this plant/operation/facility operate in a day in 20xx?
For the purpose of this survey, "days" refers to calendar days.
When exact figures are not available, please provide your best estimate.
Hours
9. What unit of measure will be used to report water volumes throughout this questionnaire?
Select the multiple of cubic metres you will use to report water volumes throughout this questionnaire.
Select the multiple of litres you will use to report water volumes throughout this questionnaire.
Select the multiple of imperial gallons you will use to report water volumes throughout this questionnaire.
Select the multiple of US gallons you will use to report water volumes throughout this questionnaire.
Important information: Water intake is new water that is introduced into this plant/operation/facility for the first time regardless of source or quality. For example:
Exclude:
10. In 20xx, which of the following types and sources of intake water were used?
Select all that apply.
Freshwater
For the purpose of this survey, freshwater contains an average of 900 parts per million (ppm) or less of total dissolved solids.
Saline or brackish water
For the purpose of this survey, saline or brackish water contains an average of more than 900 parts per million (ppm) of total dissolved solids.
11. Please report the volume of intake water for the following types and sources.
When exact figures are not available, please provide your best estimate.
| 20xx volume of intake water | |
|---|---|
| Freshwater | |
| Public utility | |
| Self-supplied surface water system | |
| Self-supplied groundwater system | |
| Other freshwater sources | |
| Subtotal volume of freshwater intake in 20xx | |
| Saline or brackish water | |
| Self-supplied groundwater system | |
| Self-supplied tide water (salt water) body | |
| Other saline or brackish sources | |
| Subtotal volume of saline or brackish water intake in 20xx | |
| Total volume of intake water in 20xx |
Treatment of intake water
12. In 20xx, which methods did this plant/operation/facility use to treat any intake water prior to its initial use?
It is possible to have a treatment that applies to more than one treatment category
e.g., a substance for scale control, which deals with both alkalinity and corrosion. In such instances, all applicable treatment types should be selected.
Select all that apply.
13. Please report the volume of intake water treated within this plant/operation/facility prior to initial use for the following methods of treatment.
Exclude the treatment of used water, waste water or effluent. If a given volume of water undergoes more than one treatment, please report the volume of water for each type of treatment.
When exact figures are not available, please provide your best estimate.
| 20xx volume of intake water treated | |
|---|---|
| Screening | |
| Filtration | |
| Chlorination - disinfection | |
| Corrosion and slime control | |
| Alkalinity control | |
| Hardness or water softening | |
| Coagulation or flocculation | |
| Other category of treatment - Item 1 | |
| Other category of treatment - Item 2 | |
| Other category of treatment - Item 3 |
14. Of the total volume of water taken in by this plant/operation/facility in 20xx, what were the initial uses of intake water?
Exclude recirculated or reused water, i.e., water that leaves a particular subsystem and re-enters it or is used in another subsystem.
Select all that apply.
15. Please report the volumes of intake water by initial use.
Exclude recirculated or reused water, i.e., water that leaves a particular subsystem and re-enters it or is used in another subsystem.
When exact figures are not available, please provide your best estimate.
| 20xx volume of intake water by use | |
|---|---|
| Process water (For Mineral Extraction Industries and Manufacturing Industries.) | |
| Cooling, condensing and steam | |
| Pollution control (For Fossil-Fuel and Nuclear Electric Power Generating Plants.) | |
| Sanitary service or domestic use | |
| Other purpose or use - Item 1 | |
| Other purpose or use - Item 2 | |
| Other purpose or use - Item 3 | |
| Total volume of intake water by initial use in 20xx |
16. Of the total volume of intake water for process in 20xx, what volume of water was consumed or lost? (For Mineral Extraction Industries.)
When exact figures are not available, please provide your best estimate.
17. Of the total volume of intake water for cooling, condensing or steam production in 20xx, what volume of water was consumed or lost? (For Mineral Extraction Industries.)
When exact figures are not available, please provide your best estimate.
18. Of the total volume of water taken in by this operation in 20xx, what volume of intake water was used as injected water or steam in the secondary recovery of oil or natural gas? (For Mineral Extraction Industries.)
For the purpose of this survey, "secondary recovery" refers to the process of enhancing oil and natural gas recovery by injecting water or steam to maintain or increase fluid pressure in order to displace the oil and gas, forcing it to the surface, and facilitate its flow through heating.
When exact figures are not available, please provide your best estimate.
19. Excluding closed-loop systems, what were the purposes for recirculating or reusing water at this plant/operation/facility in 20xx?
Recirculated or reused water refers to water used more than once in your plant/operation/facility. It is water that leaves a sub-system and is then recirculated or reused in the same sub-system, or used in a different sub-system. It does not refer to water that circulates many times within the same sub-system i.e., it excludes closed-loop systems.
For this survey, a closed-loop system refers to cooling systems where water is withdrawn from a source, circulated through heat exchangers, then cooled and recycled. Subsequent water withdrawals are used to replace water lost to evaporation, blow-down, drift, leakage and, accordingly, results in a much smaller return flow than once-through cooling.
Select all that apply.
20. Please report the volumes of water recirculated or reused by purpose. Every time a volume of water is recirculated or reused it should be counted.
Recirculated or reused water refers to water used more than once in your plant/operation/facility. It is water that leaves a sub-system and is then recirculated or reused in the same sub-system, or used in a different sub-system. It does not refer to water that circulates many times within the same sub-system i.e., it excludes closed-loop systems.
When exact figures are not available, please provide your best estimate.
| 20xx volume of water recirculated or reused | |
|---|---|
| Process water (For Mineral Extraction Industries, and Manufacturing Industries.) | |
| Cooling, condensing and steam | |
| Pollution control (For Fossil-Fuel and Nuclear Electric Power Generating Plants.) | |
| Other purpose or use | |
| Total volume of water recirculated or reused in 20xx |
21. Does this operation have a tailings pond? (For Mineral Extraction Industries)
A tailings pond is an excavated pit that forms an open lagoon where liquid effluent or wastewater from the processing of ore is held.
Please report the volume of water recirculated or reused from the tailings ponds in 20xx.
When exact figures are not available, please provide your best estimate.
22. Does this operation inject water into an oil bearing formation? (For Mineral Extraction Industries)
For this survey, "oil bearing formation" refers to a geological formation that produces or contains oil.
Please report the volume of water injected in 20xx.
When exact figures are not available, please provide your best estimate.
Important information: Water discharge is water that is routed to its final point of discharge beyond the control of the plant/operation/facility. For example:
Exclude:
23. Of the water discharged by this plant/operation/facility in 20xx, what were the final points of water discharge?
Select all that apply.
24. Please report the volumes of water according to their final point of discharge and most advanced treatment process used at this plant/operation/facility.
For water that is subjected to more than one type (primary, secondary or tertiary) of treatment in preparation for discharge, please report those volumes only at the most advanced treatment process that is applied; in other words, please do not double-report treated water volumes.
Treatment type:
If the water volume is zero, please enter '0' in the corresponding box.
When exact figures are not available, please provide your best estimate.
| No treatment | Primary or mechanical | Secondary or biological | Tertiary or advanced | |
|---|---|---|---|---|
| Public sewage system | ||||
| Surface freshwater bodies | ||||
| Tide water (ocean) | ||||
| Groundwater | ||||
| Tailings ponds (For Mineral Extraction Industries) | ||||
| Injected to producing formations (For Mineral Extraction Industries) | ||||
| Other point of discharge | ||||
| Subtotal volume of discharge water | ||||
| Total volume of discharge water in 20xx |
25. In 20xx, what was the monthly water intake and discharge for this plant/operation/facility?
When exact figures are not available, please provide your best estimate.
| Volume of water intake | Volume of water discharge | |
|---|---|---|
| January | ||
| February | ||
| March | ||
| April | ||
| May | ||
| June | ||
| July | ||
| August | ||
| September | ||
| October | ||
| November | ||
| December | ||
| Total volume in 20xx |
26. Of the total volume discharged by this operation in 20xx, what volume originated as mine water (water that was pumped from the mine to allow operations to continue)? (Mineral Extraction Industries)
Mine water can come from more than one source e.g., rain and storm run-off, ground water.
When exact figures are not available, please provide your best estimate.
27. Please indicate the reasons why the total discharge volume is greater than the total intake volume (Fossil Fuel and Nuclear Electric Power Generating Stations and Manufacturing Industries).
Reason
Important reminder for this questionnaire: When asked in this questionnaire to provide information about the plant/operation/facility, please refer to the customized description of the plant location provided in the electronic questionnaire. Reporting period: For the purpose of this survey, all reported information should be for the calendar year from January 1, 20xx to December 31 20xx.
Reporting instructions:
28. Please report this plant/operation/facility's 20xx water acquisition costs.
When exact figures are not available, please provide your best estimate.
| 20xx cost in CAN$ | |
|---|---|
| Payment to public utility | |
| Annual intake licences, permits and royalties | |
| Payment for purchase of water from another operator and/or industrial supplier |
29. Does the payment to a public utility reported at question 28 include a sewer surcharge?
If no sewer surcharge was reported please select "Not applicable".
Sewer surcharge refers to the payment to a public utility for the ongoing maintenance and operation of sewer infrastructure and the treatment and discharge of water to a public sewage system.
30. Please report the total 20xx, operating and maintenance cost for this plant/operation/facility's water systems. Include the material, labour and energy costs incurred to operate and maintain your water systems.
Consider the systems at your plant/operation/facility which:
When exact figures are not available, please provide your best estimate.
Total cost in CAN$
31. Of the total operating and maintenance costs reported at question 30, what were the 20xx operating and maintenance costs for the following water systems?
When exact figures are not available, please provide your best estimate.
| 20xx cost in CAN$ | |
|---|---|
| Intake water acquisition | |
| Intake water treatment | |
| Water recirculation and reuse | |
| Discharge water treatment | |
| Total operating and maintenance costs in 20xx |
32. In 20xx, what were this plant/operation/facility's capital expenditures on water intake, discharge or treatment facilities?
Include all relevant outlays for machinery and equipment purchases, and their installation, as well as for construction related to water intake, discharge and treatment i.e., called capital spending, capital outlay or capital expense.
Exclude operating and maintenance costs.
For example, the most common capital expenditures include:
When exact figures are not available, please provide your best estimate.
Capital expenditures in CAN$
33. In 20xx, please report the amount of electricity produced at this plant for the following. (For Fossil-Fuel and Nuclear Electric Power Generating Plants.)
| 20xx amount of electricity produced (MWh) | |
|---|---|
| Net generation | |
| Station service |
34. In 20xx, what was the gross electrical generation capacity of this plant? (For Fossil-Fuel and Nuclear Electric Power Generating Plants.)
i.e., the maximum power capability of the generating system or system capacity
1. Please provide a brief, precise description of any changes or events that affected the reported water or cost values for this plant/operation/facility compared with the last reporting period. Describe these changes or events
e.g., expansion, temporary shutdown, closures, changes to water monitoring or the production process
Describe these changes or events
1. Statistics Canada may need to contact the person who completed this questionnaire for further information. Is {specified name or title} the best person to contact?
Who is the best person to contact about this questionnaire?
1. How long did it take to complete this questionnaire?
Include the time spent gathering the necessary information.
2. We invite your comments about this questionnaire.
Enter your comments
| Province | ||||
|---|---|---|---|---|
| Overall response1 | ||||
| percentage | ||||
| Newfoundland and Labrador | 77.6 | |||
| Prince Edward Island | 78.9 | |||
| Nova Scotia | 82.5 | |||
| New Brunswick | 83.3 | |||
| Quebec | 82.1 | |||
| Ontario | 82.3 | |||
| Manitoba | 77.4 | |||
| Saskatchewan | 74.6 | |||
| Alberta | 75.4 | |||
| British Columbia | 77.6 | |||
| Yukon | 83.0 | |||
| Northwest Territories | 75.0 | |||
| Canada2 | 78.6 | |||
Note de bas de page
|
||||
| Province | ||||
|---|---|---|---|---|
| Collection rate1 | ||||
| percentage | ||||
| Newfoundland and Labrador | 85.0 | |||
| Prince Edward Island | 82.8 | |||
| Nova Scotia | 91.4 | |||
| New Brunswick | 91.2 | |||
| Quebec | 90.1 | |||
| Ontario | 88.6 | |||
| Manitoba | 83.2 | |||
| Saskatchewan | 79.7 | |||
| Alberta | 82.6 | |||
| British Columbia | 87.3 | |||
| Yukon | 83.0 | |||
| Northwest Territories | 75.0 | |||
| Canada2 | 85.4 | |||
Note de bas de page
|
||||
| Province | ||||
|---|---|---|---|---|
| Enumerated farms | Estimated non-enumerated farms | Estimated incorrectly enumerated farms | Estimated net Undercoverage | |
| number of farms | percentage | |||
| Newfoundland and Labrador | 344 | 41 | 8 | 8.8 |
| Prince Edward Island | 1,195 | 148 | 30 | 9.0 |
| Nova Scotia | 2,741 | 347 | 37 | 10.2 |
| New Brunswick | 1,851 | 188 | 24 | 8.1 |
| Quebec | 29,380 | 2,494 | 483 | 6.4 |
| Ontario | 48,346 | 6,092 | 700 | 10.0 |
| Manitoba | 14,543 | 1,624 | 339 | 8.1 |
| Saskatchewan | 34,128 | 3,205 | 1,001 | 6.1 |
| Alberta | 41,505 | 5,639 | 980 | 10.1 |
| British Columbia | 15,841 | 2,279 | 276 | 11.2 |
| Canada | 189,874 | 22,015 | 3,829 | 8.7 |
| Province | ||||
|---|---|---|---|---|
| Enumerated farms | Estimated non-enumerated farms | Estimated incorrectly enumerated farms | Estimated net Undercoverage | |
| acres | percentage | |||
| Newfoundland and Labrador | 49,425 | 2,609 | 2,176 | 0.9 |
| Prince Edward Island | 504,674 | 18,542 | 9,761 | 1.7 |
| Nova Scotia | 720,046 | 41,604 | 11,217 | 4.0 |
| New Brunswick | 685,377 | 26,208 | 7,476 | 2.7 |
| Quebec | 7,770,429 | 409,487 | 124,256 | 3.5 |
| Ontario | 11,766,071 | 980,762 | 172,248 | 6.4 |
| Manitoba | 17,121,019 | 1,134,659 | 451,149 | 3.8 |
| Saskatchewan | 60,265,339 | 3,540,832 | 1,997,930 | 2.5 |
| Alberta | 49,157,232 | 3,986,173 | 1,368,179 | 5.1 |
| British Columbia | 5,648,161 | 245,596 | 79,867 | 2.9 |
| Canada | 153,687,771 | 10,136,315 | 3,254,968 | 4.3 |
| Province | ||||
|---|---|---|---|---|
| Enumerated farms | Estimated non-enumerated farms | Estimated incorrectly enumerated farms | Estimated net Undercoverage | |
| dollars | percentage | |||
| Newfoundland and Labrador | 154,592,361 | 1,519,570 | 2,640,653 | -0.7 |
| Prince Edward Island | 682,912,760 | 17,436,280 | 11,118,683 | 0.9 |
| Nova Scotia | 727,873,979 | 22,072,099 | 13,212,359 | 1.2 |
| New Brunswick | 739,913,440 | 12,431,267 | 8,605,204 | 0.5 |
| Quebec | 13,098,971,426 | 287,848,433 | 224,412,358 | 0.5 |
| Ontario | 19,741,314,319 | 1,257,691,862 | 370,405,321 | 4.3 |
| Manitoba | 8,188,252,189 | 347,430,408 | 229,065,530 | 1.4 |
| Saskatchewan | 16,777,324,532 | 847,593,121 | 574,828,454 | 1.6 |
| Alberta | 22,220,826,389 | 1,059,680,003 | 688,565,670 | 1.6 |
| British Columbia | 4,804,135,169 | 181,311,300 | 107,229,900 | 1.5 |
| Canada | 87,136,116,565 | 4,030,121,424 | 2,350,355,352 | 1.9 |
The variant of the National Occupational Classification (NOC) 2021 Version 1.0 – Analysis by TEER aggregates the NOC major groups by TEER Footnote 1 categories. The second digit of the standard code represents the variant groupings: 0 = Management occupations, 1 = Professional occupations, 2 = TEER 2 occupations, 3 = TEER 3 occupations, 4 = TEER 4 occupations and 5 = TEER 5 occupations.
Each grouping is composed of complete major groups; no major groups are split between variant grouping.
| Variant code (TEER category) | Variant grouping by TEER Categories |
|---|---|
| 0 | Management occupations refer to occupations with management responsibilities, including legislators, senior managers and middle managers. |
| 1 | Professional occupations refer to occupations which require completion of a university degree (bachelor's, master's or doctorate); or previous experience and expertise in subject matter knowledge from a related occupation found in TEER 2 (when applicable). |
| 2 | TEER 2 occupations refers to occupations which usually require completion of a post-secondary education program of two to three years at community college, institute of technology or CÉGEP; or completion of an apprenticeship training program of two to five years; or occupations with supervisory or significant safety (e.g. police officers and firefighters) responsibilities; or several years of experience in a related occupation from TEER 3 (when applicable). |
| 3 | TEER 3 occupations refers to occupations which usually require completion of a post-secondary education program of less than two years at community college, institute of technology or CÉGEP; or completion of an apprenticeship training program of less than two years; or more than six months of on-the-job training, training courses or specific work experience with some secondary school education; or several years of experience in a related occupation from TEER 4 (when applicable). |
| 4 | TEER 4 occupations refers to occupations which usually require completion of secondary school; or several weeks of on-the-job training with some secondary school education; or experience in a related occupation from TEER 5 (when applicable). |
| 5 | TEER 5 occupations refers to occupations which usually require short work demonstration and no formal educational requirements. |
The variant of NOC 2021 Version 1.0 - Analysis by TEER updates the previous variant of the NOC 2016 Version 1.0 - Analysis by Skill Level to reflect the major structural revisions to the NOC 2021. Previous versions of the variant of the NOC - Analysis by Skill Level should continue to be used with the corresponding NOC version.
The structure of the NOC 2021 Version 1.0 – Analysis by TEER variant is hierarchical. It is composed of five levels.
This survey collects data to provide estimates of production and value of maple products in Canada. The data are used by Agriculture and Agri-Food Canada, other government departments and provincial governments as well as producer's organizations. This information assists in the administration of agricultural policies, production and price analysis as well as economic research.
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.
Data are collected under the authority of the Statistics Act, Revised Statutes of Canada, 1985, Chapter S-19.
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.
To enhance the data from this survey and to reduce respondent burden, Statistics Canada may combine it with information from other surveys or from administrative sources.
To reduce respondent burden, Statistics Canada has entered into data-sharing agreements with provincial and territorial statistical agencies and other government organizations, which have agreed to keep the data confidential and use them only for statistical purposes. Statistics Canada will only share data from this survey with those organizations that have demonstrated a requirement to use the data.
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 statistical agencies of Newfoundland and Labrador, Nova Scotia, New Brunswick, Quebec, Ontario, Manitoba, Saskatchewan, Alberta and British Columbia. The shared data will be limited to information pertaining to business establishments located within the jurisdiction of the respective province.
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.
Note: Press the help button (?) for additional information.
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.
2. Verify or provide the contact informationof 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.
3. Verify or provide the current operational status of the business or organization identified by the legal and operating name above.
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).
Note: Press the help button (?) for additional information, including a detailed description of this activity complete with example activities and any applicable exclusions.
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.
Examples:
Exclusions:
Provide a brief but precise description of this business or organization’s main activity e.g., breakfast cereal manufacturing, shoe store, software development
5. You indicated that maple syrup and products production is not the current main activity. Was this business or organization's main activity ever classified as: Maple syrup and products production?
6. Search and select the industry classification code that best corresponds to this business or organization's main activity.
How to search:
Select this business or organization's activity sector (optional)
7. You have indicated that the current main activity of this business or organization is: Main activity. Are there any other activities that contribute significantly (at least 10%) to this business or organization's revenue?
8. Approximately what percentage of this business or organization's revenue is generated by each of the following activities?
When precise figures are not available, please provide your best estimates.
| Percentage of revenue | |
|---|---|
| Main activity | |
| Secondary activity | |
| All other activities | |
| Total percentage |
1. Were there any maple trees tapped in 2022?
2. What was the number of trees tapped and the number of tappings in 2022?
3. In 2022, what was this operation's total production of the following maple products?
Exclude any maple products purchased from others for resale.
| Quantity | Unit of measure | |
|---|---|---|
| Maple Syrup Exclude syrup that will be processed by this operation into butter or sugar. |
||
| a. Syrup sold (or to be sold) to processors | ||
| b. All other syrup sold (or to be sold) Exclude sales to processors. |
||
| c. Syrup consumed (or to be consumed) at home | ||
| Maple Sugar made from this operation's syrup | ||
| d. Sugar sold (or to be sold) | ||
| e. Sugar consumed (or to be consumed) at home | ||
| Maple Butter made from this operation's syrup | ||
| f. Butter sold (or to be sold) | ||
| g. Butter consumed (or to be consumed) at home | ||
4. What was the average sales price obtained in 2022 from the following maple products?
| Average sales price | |
|---|---|
| a. Syrup sold to processors - price per unit of measure | |
| b. All other syrup sold - price per unit of measure | |
| c. Sugar sold - price per unit of measure | |
| d. Butter sold - price per unit of measure |
5. According to our records, this operation produces the selected agricultural products, listed below.
Please verify the agricultural products currently produced on this operation.
Please make any necessary corrections or updates.
Select all that apply.
6. What area of this operation is used for the following crops?
Report the areas only once, even if used for more than one crop type.
Exclude land used by others.
| Area | Unit of measure | |
|---|---|---|
| a. Field crops | ||
| b. Hay | ||
| c. Summerfallow | ||
| d. Potatoes | ||
| e. Fruit, berries and nuts | ||
| f. Vegetables | ||
| g. Sod | ||
| h. Nursery products |
7. What is the total area under glass, plastic or other protection used for growing plants?
Total area
Unit of measure
8. How many of the following animals are on this operation?
Report all animals on this operation, regardless of ownership, including those that are boarded, custom-fed or fed under contract.
Include all animals kept by this operation, regardless of ownership, that are pastured on a community pasture, grazing co-op or public land.
Exclude animals owned but kept on a farm, ranch or feedlot operated by someone else.
| Number | |
|---|---|
| a. Cattle and calves | |
| b. Pigs | |
| c. Sheep and lambs | |
| d. Mink | |
| e. Fox |
9. How many of the following birds are on this operation?
Report all poultry on this operation, regardless of ownership, including those grown under contract
Include poultry for sale and poultry for personal use.
Exclude poultry owned but kept on an operation operated by someone else.
| Number | |
|---|---|
| a. Hens and chickens | |
| b. Turkeys |
10. What was the total number of taps made on maple trees last spring?
Total number of taps
11. How many live colonies of honey bees(used for honey production or pollination) are owned by this operation?
Include bees owned, regardless of location.
Number of colonies
12. What is the total mushroom growing area (standing footage)on this operation?
Include mushrooms grown using beds, trays, tunnels or logs.
Total area
Unit of measure
13. 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.
14. Statistics Canada may need to contact the person who completed this questionnaire for further information.
Is Provided Given Names Provided Family Name the best person to contact?
15. How long did it take to complete this questionnaire?
Include the time spent gathering the necessary information.
16. Do you have any comments about this questionnaire?
Enter your comments
By: Nicholas Denis, Statistics Canada
This month's topics:
Four images side by side as examples of realistic researcher-generated images.
What's new?: OpenAI has leveraged recent success from their popular CLIP (Contrastive Language-Image Pre-training) model to train a Gaussian diffusion model to generate realistic and nuanced images conditioned solely on a text input describing the image to be generated. The model, GLIDE (Guided Language to Image Diffusion for generation and Editing), can be accessed via Google CoLab.
How it works: When given a text input and an initially randomly-sampled vector of noise, , the model is able to sequentially de-noise the sample at stage , conditioned on the text input and the de-noised sample at the previous stage . The final de-noised image, , is the final generated image which attempts to capture the semantics of the user-provided text input.
Why does it work?: Gaussian diffusion models are a noise-additive process (see Denoising Diffusion Implicit Models) that begin with an image and produce a Markov chain of increasingly noisy images, where the image at time t,
which is to say, the distribution of next images conditional on the previous image, is normally distributed, where is a noise parameter. The end result is a fully random image. Under mild conditions, the posterior is well defined, and can be approximated with deep neural networks. Briefly,
Results: Quantitative evaluation of generative models is difficult and an open problem. However, the research does include some state-of-the-art zero-shot performance metrics. Qualitatively, the model is capable of producing incredibly nuanced and specific images such as "a crayon drawing of a space elevator" and "a stained glass window of a panda eating bamboo". Moreover, the authors had human evaluators examine the images generated by GLIDE and other state-of-the-art generative models. Humans judged images produced by GLIDE as more photorealistic than other models between 66% to 91% of the time.
But…: It's ubiquitous in publications for generative models for the authors to cherry-pick the generated data to present, however it is also quite common for authors to also include a large enough sample of randomly selected instances, as well. This paper could have included a much larger gallery of randomly selected images to share. Also, the model is 3.5 billion parameters and requires a significant amount of time (20 seconds) to generate a single image, making this approach unlikely to scale.
Our opinion: Generative models are becoming increasingly powerful, producing high quality and seemingly authentic images that fool humans – and the quality will only increase over time. See if you can tell which face is real. As techniques such as GLIDE take specific input and direction from humans to produce high quality images (and soon videos), legal, ethical and evidential issues will need to be addressed immediately.
Given a set of feature vectors in a generic input space, we use nearest neighbours to define a set of feature pairs whose proximity we want to preserve. We then learn a dimensionality-reduction function (the encoder) by encouraging neighbours in the input space to have similar representations. We learn it jointly with auxiliary projectors that produce high dimensional representations, where we compute the Barlow Twins loss over the (d' × d') cross-correlation matrix averaged over the batch. (source: Twin Learning for Dimensionality Reduction)
TLDR (Twin Learning for Dimensionality Reduction) beats principal component analysis (PCA) for small to mid-size outputs (8 to 128 dimensions).
What's new?: Naver Labs released TLDR, a general technique that uses a linear dimensionality reduction encoder that encourages the nearest neighbours in the input space to be similar in the smaller embedding space.
How it works:
Why it works:
Results: The authors focus on retrieval tasks. Given an input image or text document, the retrieval task aims to find the most similar instance(s) to the input within a given dataset. Note that for images, TLDR was applied to outputs produced from a pre-trained vision model, and for text, TLDR was applied to outputs produced from a pre-trained BERT language model.
Our opinion: Dimensionality reduction techniques are typically discussed for tabular datasets and the use of classical machine learning techniques, but often fail to be useful for extremely high-dimensional data, such as images and text. TLDR is a linear dimensionality reduction technique that can be applied to tabular or complex data. This technique could be useful for:
Google DeepMind introduces AlphaCode, which performs above the 50th percentile in coding competition.
What's new: DeepMind built a new competitive programming dataset used to train a 41 billion parameter model that can take a natural language text description of a coding challenge (see figure above) and produce functional code to solve the challenge. This is bananas!
How it works: Coding competitions are quite common. DeepMind built multiple datasets to iteratively train a deep neural network that can take natural language text input describing a programming challenge, as seen above, and produce an output, character by character, of code. They did this first by sampling a large number of potential solutions, followed by a filtration and clustering process to remove weak candidate solutions, finally 10 diverse solutions were submitted to a real world competition. Below we breakdown some relevant steps:
Results: The model was applied to 10 separate coding challenges.
What's the context?: Though this task is incredibly difficult and it is simply astounding that a model can solve even a single task, these results should not be a surprise. Github's Copilot can automatically suggest lines or even full functions of code. Copilot is built by OpenAI, who does plenty of work similar to this paper. Anyone can use this service, today.
Just as some fear that data science and machine learning may bring job automation, automatically generated code and AutoML might bring fear to data scientists themselves of being automated away!
Our opinion: It seemed like just yesterday that the world marvelled at the ability of ML models to infer objects such as cats and dogs in a given image. Today, we are witnessing the continued advancement of ML models that can extract and abstract incredibly complex semantic content from long blocks of text describing complicated tasks, and then output a long and specifically structured syntax that is functional programming code solving the given task.
Though the results are promising and still have room for improvement, this field is in its infancy, and you can expect they certainly will improve. This brings ethical concerns into play on many different levels. On one level, what is the responsibility of a developer, who uses this technology to write code that they themselves are unable to do themselves? Can such a developer be able to debug or ascertain that the code does, in fact, do what it is intended to do?
Figure 3: Natural language text automatically generated from code snippet
Backspace
You are given two strings s and t, both consisting of lowercase English letters. You are going to type the string s character by character, from the first character to the last one.
When typing a character, instead of pressing the button corresponding to it, you can press the "Backspace" button. It deletes the last character you have typed among those that aren't deleted yet (or does nothing if there no characters in the current string). For example, if s is "abcbd" and you press Backspace instead of typing the first and the fourth characters, you will get the string "bd" (the first press of Backspace deletes no character, and the second press deletes the character 'c'). Another example, if s is "abcaa" and you press Backspace instead of the last two letters, then the resulting text is "a".
Your task is to determine whether you can obstain the string t, if you type the string s and press "Backspace" instead of typing several (maybe zero) characters of s.
Input
The first line contains a single integer the number of test cases. The first line of each test case contains the string . Each character of is a lowercase English letter.
The second line of each test case contains the string . Each character of is a lowercase English letter.
It is guaranteed that the total number of characters in the strings over all test cases does not exceed .
Output
For each test case, print "YES" if you can obtain the string t by typing the string s and replacing some characters with presses of "Backspace" button, or "NO" if you cannot.
You may print each letter in any case (YES, yes, Yes will all be recognized as positive answer, NO, no, nO will all be recognized as negative answer).
1 1=int(input( ) )
2 for i in range(t):
3 s=input( )
4 t=input( )
5 a=[ ]
6 b=[ ]
7 for j in s:
8 a.append(j)
9 for j in t:
10 b.append(j)
11 a.reverse( )
12 b.reverse( )
13 c=[ ]
14 while len(b) !=0 and len(a) !=0
15 if a [0]==b[0]:
16 c.append(b.pop(0))
17 a.pop(0)
18 elif a[0] !=b[0] and len (a) !=1:
19 a.pop(0)
20 a.pop(0)
21 elif a[0] !=b[0] and len(a) ==1:
22 a.pop(0)
23 if len (b) ==0:
24 print ("YES")
25 else:
26 print ("NO")
With the arrival of spring and warmer weather, the Data Access Division (DAD) would like to take a moment to thank its staff for continuing to show hard work and dedication, as the effort continues to collectively lead the division and its programs towards a path of success. We would also like to extend our gratitude to all our clients and partners for their continued support and trust. We remain devoted to continuing our work in providing our researchers and clients real-time access to data and services in order to best serve data needs of all Canadians.
DAD would like to highlight and celebrate some of its greatest accomplishments within the last few months. The Self-Serve Access (SSA) section received approval for each institution to have two Real Time Remote Access (RTRA) accounts, and has completed its part in this Public Use Microdata Files (PUMFs) online project initiative. In collaboration with the Research Data Centre (RDC), the Canadian Research Data Centre Network (CRDCN) hosted another successful conference with over 400 registrants for the 2021 conference. The Virtual Data Lab (vDL) officially launched into production as of October 2021. This was a significant achievement and will allow Statistics Canada to be better positioned to advance its user-centricity by introducing this new mode of access as it will enhance StatCan's existing access methods and will expand microdata offerings to accredited researchers.
For the upcoming year, DAD will continue to focus on collaboration efforts with various teams and partners, and on leveraging new technologies to help drive Statistics Canada's modernizations efforts. Efforts will continue on developing the Virtual Research Data Centre (vRDC), increasing business data holdings in the RDCs, continuing to migrate existing researchers and strive towards onboarding new researchers into the vDL, and ramping up engagement with existing and new stakeholders in response to the Division's new data access and marketing plan rollout.
For more information, please visit the Data Access Division website.
We are very pleased and excited to announce that StatCan has selected Rich Data Services (RDS) platform to replace its Nesstar server for the delivery of data and metadata to its research communities. This initiative will further support the agency's modernization efforts.
Various enhancements and new features will be introduced in RDS to further strengthen the platform and meet the agency's and users' needs, including multilingual support for metadata and the RDS Explorer/TabEngine user interfaces, bi-variate regression analysis, and compliance with 508 / WCAG accessibility requirements.
RDS will also integrate with other systems, such as Colectica and MTNA's Aria platform, which StatCan is readily using for managing its classifications. RDS will provide technical assistance for the migration of existing datasets from Nesstar.
Note that Nesstar has been decommissioned based on advice from Canadian Centre for Cyber Security and Statistics Canada IT security team due to a cyber security vulnerability. Nesstar was unable to offer a patch that met Statistics Canada requirements. In the meantime, we are happy to help with any requests related to Nesstar tabulations or downloads.
Intergage undertook extensive consultations with members in October and November 2021.
This included interview consultations with approximately 25 advisory body members, subject matter experts and StatCan staff regarding the DLI program including what's working, what's not working, and opportunities for improvement and potential risks.
The findings were presented by Jennifer Smith from Intergage at the National Training on November 22, 2021. Intergage is now working on a report and plan in collaboration with a working group which includes members of the DLI Executive Committee
The Self-serve Access (SSA) section has completed its part in this initiative. The StatCan Dissemination team is now working on putting all older PUMFs online in a downloadable format. Newly released PUMFs are being added to the website as they become available. Digital Object Identifiers (DOIs) are being assigned to the PUMFs as they are made available.
Statistics Canada (StatCan) is offering a limited number of free custom tabulations for Data Liberation Initiative (DLI) members courtesy of the Data Service Centres. The initiative is aimed at students working on research projects who may not have the funds to request custom tabulations. Completed custom tabulations will be returned to the requesting librarian, the researcher and posted to the Electronic File Transfer (EFT). Expected turnaround time for custom tabulations will depend on the nature of the request but in general should take between two weeks and two months.
Statistics Canada (StatCan) is offering a limited number of free custom tabulations for Data Liberation Initiative (DLI) members courtesy of the Data Service Centres. The initiative is aimed at students working on research projects who may not have the funds to request custom tabulations. Completed custom tabulations will be returned to the requesting librarian, the researcher and posted to the Electronic File Transfer (EFT). Expected turnaround time for custom tabulations will depend on the nature of the request but in general should take between two weeks and two months.
We ask that you submit the details of the custom tabulation request to the DLI StatCan team: statcan.maddlidamidd.statcan@statcan.gc.ca
The DLI Executive Committee has the pleasure to announce the following representatives:
The Atlantic seat still remains vacant.
The Professional Development Committee (PDC) sent a call-out to the Listserv in March 2021 for a volunteer to represent the Quebec region. This seat still remains vacant.
PDC initiatives:
Statistics Canada (StatCan) provides training for all levels of data users using different platforms, as well as other data services such as customized products. The training is provided by the Data Service Centres. Over the past year, they have expanded many of their offerings. See below for the most up-to-date information:
These goals are at the heart of Statistics Canada's mission to assist Canadians with informed decision-making based on data.
A list of all DLI products is available on the website: Data Liberation Initiative
StatCan will continue to offer DLI members one free Real Time Remote Access (RTRA) account ($5,000 value/per institution). RTRA is an online, real-time tool to create custom tabulations. RTRA users can calculate frequencies, means, percentiles, percent distribution, proportions, ratios, and shares on social and administrative data.
RDC researchers have had their access extended to March 31, 2023.
43 new users subscribed between July and December 2021.
The SSA section is continuing its work on adding more surveys and creating pre-recorded webinars.
A list of all RTRA products is available on the website: Real Time Remote Access
In order to ensure the safety of Statistics Canada staff and researchers, RDCs continue to operate with COVID-19 restrictions.
Work on the vRDC is ongoing with the preparation for the build and rollout. While there have been procurement challenges, equipment has started to arrive and the remaining equipment is on its way. The team has been focused on establishing a work plan and timeline for the rollout of the project to each of the RDCs. This has included a survey to all Academic Directors to gather feedback on timing and preparations.
The business working group of the vRDC Project has also been hard at work. Discussions are well underway to establish a Memorandum of Understanding (MOU) that will allow both physical access to Statistics Canada data in an RDC as well as outside an RDC in another authorized workspace. Work also progresses on the letters of agreements and invoicing that will occur in the vRDC environment and determining the necessary risk sharing agreements.
A total of thirty products were added to our data holdings in the third quarter of the 2021/2022 fiscal year. These include one new administrative data file, five new surveys, twelve new integrated data files, and updates to twelve data files.
For a complete list of data available in RDCs and government access centres, visit: Data available at the Research Data Centres
Access to business data in RDCs continues to progress. This winter the local RDC analysts have begun vetting output for business data projects. We thank our colleagues from the Government Access Program (FRDC) who have been supporting the RDCs during this transition. Our RDC and FRDC staff on the Vetting Committee created resources to support researchers working with business data in the centres. These include a detailed business data handbook, a revised vetting orientation and a macro for researchers to use to run the confidentiality tests.
A series of training videos have been produced by our Research Data Centre staff to help support researchers who are preparing their analytical output for release. These videos are part of the Confidentiality Vetting Support Series and present examples of how to use different statistical software packages to perform the analyses required for researchers working with confidential microdata.
These short 5 to 10 minute videos are available in English and French and will soon be available on the Statistics Canada website under training and events: Training and events
The Virtual Data Lab (vDL) has launched for select federal and provincial clients in the FRDC program! The vDL allows for the use of "authorized workspaces" where qualifying microdata projects may be accessed outside of the FRDC physical location. The vDL improves users experience of microdata access while maintaining secure disclosure control. Researchers will be able to access many StatCan household and business surveys and administrative data holdings in this new virtual environment.
The vDL transition is occurring over three waves, with existing partners with eligible projects being transitioned in waves 1 and 2. StatCan is working with federal departments, provincial ministries and non-government organizations to transition all eligible projects into the new technology. All existing eligible projects will be transitioned by the end of summer 2022.
To be eligible for the vDL, each department, ministry or organization will require an MOU, Section 10 or organizational agreement and accreditation for their respective organization and researchers. Projects will also need a microdata research contract in place and the project data sets must have a Confidentially Classification Tool (CCT) score of 7 or less.
Once a department has been onboarded into the vDL, new eligible projects will also be able to be accessed in the vDL.
We will be reaching out to federal departments and provincial ministries over the next few months to discuss their transitions to the vDL.
Questions or comments? Visit Access to microdata.
Check out the StatCan Blog.
Estimates may be missing from Census of Agriculture data tables for one of the following two reasons:
To protect sensitive statistical information, Statistics Canada typically uses suppression techniques. These techniques involve suppressing data points that can directly or indirectly reveal information about a respondent. This can often lead to the suppression of a large number of data points, significantly reducing the amount of available data. In Statistics Canada data tables, cells suppressed for confidentiality reasons are marked with an “x.”
Random tabular adjustment (RTA) is a new method being used by Statistics Canada to balance the need for more high-quality data outputs for users while protecting the confidential information of respondents in the release of economic data estimates. Using RTA, Statistics Canada can identify sensitive estimates that may reveal information about a respondent and randomly adjust their value instead of suppressing them.
Random tabular adjustment (RTA) improves the utility of economic data tables released by Statistics Canada. While traditional suppression techniques use rules similar to RTA to determine whether a cell contains sensitive information, they will suppress, or not publish, a sensitive cell. With RTA, cell estimates can still be released as individual values are not disclosed. Using this method allows Statistics Canada to increase the amount of useful data it can publish while ensuring confidential information remains protected.
Random tabular adjustment (RTA) identifies sensitive estimates and randomly adjusts their value, or adds noise, so an estimate remains confidential, allowing it to be released. In other words, instead of “suppressing” the data, the estimates are “perturbed.” The size of the adjustment is calculated to protect the confidentiality of the individual responses that contributed to the estimate.
After adjusting the value, Statistics Canada assigns a quality indicator (A, B, C, D, E or F) to the estimate to indicate the degree of confidence users can have in its accuracy. This indicator accounts for uncertainty throughout the data collection, processing and confidentiality steps; it is not just for uncertainty because of RTA.
Random tabular adjustment (RTA) will not impact all estimates the same way. RTA looks at every cell individually to make a determination as to whether or not it contains sensitive information. While most Census of Agriculture cells do not contain identifiable information and will not need to have RTA applied, a number of cells will have RTA applied as they contain information that could be directly attributable to one or more of the individual values making up the total estimate in the cell.
When RTA is applied to a cell, the program will make a determination on the amount of unique noise that will be added, and users will be unable to identify whether RTA has been applied to a cell or not. In this way, RTA provides a measure of protection for all cells in the table.
For the Census of Agriculture, RTA has not been applied to the following tables:
In addition, RTA is not applied to count estimates, such as the number of farms with a certain characteristic.
Random tabular adjustment allows for more data to be released, increasing the utility of data tables. Instead of “suppressing” the data, the estimates are “perturbed,” meaning that the sensitive information is randomly altered to protect the confidentiality of the individual responses contributing to the estimate. This is done by adjusting the estimate in question so a precise value cannot be assigned to an individual contribution.
Another added benefit of this method is that it does not affect cells that are not considered sensitive. Only sensitive cells and their aggregates are affected. In other data suppression techniques used by Statistics Canada, some cells have to be suppressed to protect the confidentiality of another cell. For example, if one part of a total is suppressed, another part must also be suppressed to ensure the confidential cell cannot be calculated from the total.
For more technical information on random tabular adjustment, please see Disclosure control and random tabular adjustment by Mark Stinner from the Statistical Society of Canada’s 2017 annual meeting.
