PUMF Program Subscription Form

PUMF Program Subscription Form – Membership Agreement (PDF, 315.75 KB)

Between His Majesty the King in Right of Canada, as represented by the Minister of Innovation, Science and Economic Development, having been designated as the Minister for the purposes of the Statistics Act (referred to herein as "Statistics Canada"),

And:

  • Name of the other party,
  • Hereinafter called the "Licensee"

Whereas His Majesty the King in Right of Canada is the lawful owner of the Public Use Microdata Files to be licensed;

And whereas the Licensee wishes to use the Public Use Microdata Files;

Now therefore the Parties agree as follows:

Definition

1. "Public Use Microdata File" means a non-identifiable data set containing characteristics pertaining to surveyed units as described in section 2.

Description of product

2. This agreement relates to the Public Use Microdata File Collection (hereinafter called the "Collection"). The Collection contains Public Use Microdata Files released by Statistics Canada and related documentation for surveys as defined on the collection portal of the Statistics Canada website at Public Use Microdata File Collection.

Contact and custodian

3. (1) The Licensee hereby nominates [person] as the contact person to whom all further communication shall be addressed on any matter concerning this agreement; and as the designated custodian of the Collection with responsibility for ensuring its proper use and custody pursuant to the terms of this agreement.

(2) The contact information for the contact person and custodian referred to in subsection (1) may be advertised on the Collection page of the Statistics Canada website at Public Use Microdata File Collection.

Effective date and term

4. This Agreement comes into force when signed by both Parties and shall continue for an initial term ending March 31, [year]. Thereafter, the term shall be automatically extended for succeeding periods of one (1) year, unless terminated in accordance herewith.

Payment

5. (1) The Licensee agrees to pay an annual service fee of $10,000 to access the Collection. The first payment will be due to Statistics Canada on signing of this agreement. Subsequent payments will be made at the latest thirty (90) days after the expiration of the previous term (April –June).

(2) The following methods of payment are accepted; Cheque / Money Order (non-federal clients); Credit Card (MasterCard), (Visa) or (American Express) (non-federal clients); Federal Government of Canada Interdepartmental Settlement (federal clients); Direct Deposit (non-federal clients) or Bill Payment service (BPS) with Canadian bank Institutions).

(3) All cheque payments shall be made payable to the Receiver General for Canada and sent to:

Statistics Canada
Finance, 6th Floor, RH Coats Building
100 Tunney's Pasture Driveway
Ottawa, Ontario
K1A 0T6

Delivery

6. Upon execution of this agreement and payment of the annual service fee prescribed in Section 5, Statistics Canada shall provide the Licensee with password access to the Collection and related documentation.

Use of microdata

7. The Use of the Microdata is governed by Statistics Canada Open Licence, see: Statistics Canada Open Licence. For any questions regarding the Statistics Canada Open Licence see: Statistics Canada Open Licence FAQs.

Termination

8. (1) Statistics Canada will terminate this agreement automatically and access to the Collection will be revoked if the Licensee fails to comply with any of the terms of this agreement.

(2) Either party may terminate this agreement, without cause, by providing 10 days written notice. The termination shall become effective and access to the Collection will be revoked at the date mutually agreed to by both parties.

(3) Where this Agreement is terminated pursuant to subsection (1), the Licensee shall immediately take measures to terminate all use of the Collection by its users, destroy all copies of the data and related documentation and certify this destruction in writing to Statistics Canada.

Notices

9. Any notice to be given to Statistics Canada or the Licensee shall be sent to statcan.dadpumf-dadfmgd.statcan@canada.ca.

Amendment

10. No amendment to this Agreement shall be valid unless it is reduced to writing and signed by the Parties hereto.

Entire Agreement

11. This Agreement constitutes the entire agreement between Statistics Canada and the Licensee with respect to Licensee's right to use the Collection.

Appropriate law

12. This Agreement shall be governed and construed, in accordance with the laws of the province of Ontario and the laws of Canada applicable herein.

Approved by:

  • Signature
  • Date

Chief, Data Access Division

And By:

  • Name of Institution
  • Print name of authorized representative
  • Signature
  • Date
  • Name of Institution
  • Address
  • Institution's IP Range and/or Proxy Range
  • Subscription Start Date

Licence Administrator:

  • Name
  • Title
  • Phone number
  • Email address

Contact:

  • Name
  • Title
  • Phone number
  • Email address

Alternate:

  • Name
  • Title
  • Phone number
  • Email address

Repair and Maintenance Services: CVs for operating revenue - 2019

CVs for operating revenue - 2019
Table summary
This table displays the results of CVs for operating revenue - 2019. The information is grouped by Geography (appearing as row headers), CVs for operating revenue, Automotive repair and maintenance and Electronic, commercial and industrial machinery and equipment repair and maintenance, calculated using percent units of measure (appearing as column headers).
Geography Automotive repair and maintenance  Electronic, commercial and industrial machinery and equipment repair and maintenance
percent
Canada 0.91 1.73
Newfoundland and Labrador 3.56 1.57
Prince Edward Island 1.95 3.80
Nova Scotia 1.95 2.59
New Brunswick 0.59 1.55
Quebec 2.70 4.36
Ontario 1.73 4.83
Manitoba 1.46 4.83
Saskatchewan 2.00 5.23
Alberta 0.89 2.68
British Columbia 2.04 2.95
Yukon 0.61 0.47
Northwest Territories 0.00 0.00
Nunavut 0.00 50.29

First Data Science Network Directors' Committee Meeting

By: Allie MacIsaac, Statistics Canada

On November 25, 2020, senior managers involved in many facets of data science gathered (virtually, of course!) for the first directors' committee meeting of the Data Science Network for the Federal Public Service. This meeting was an important stepping stone for the Network, as it continues to grow and expand its reach in the public service and beyond.

Participants represented a broad range of departments and partners: Bank of Canada; Canada Border Services Agency; Environment and Climate Change Canada; Department of National Defense; Employment and Social Development Canada; Industry Canada; Immigration, Refugee and Citizenship Canada; Public Health Agency of Canada; National Research Council Canada; Natural Resources Canada; Privy Council Office; Public Service Commission; Statistics Canada; Shared Services Canada; Transport Canada; and Treasury Board of Canada Secretariat.

Statistics Canada, the agency spearheading the network, conducted the meeting. Opening remarks were provided by André Loranger, Assistant Chief Statistician of Analytical Studies, Methodology and Statistical Infrastructure at Statistics Canada. André noted that "the federal public service needs to adapt now to address society's growing need for timely analytical outputs to support Canadians and policy makers."

The opening remarks were followed by a presentation featuring the network's goals, objectives and areas of focus.

Goals and objectives

The goal of the Data Science Network is to establish the foundations of a public-service-wide data science ecosystem.

How will this be achieved? The Network aims to:

  • Build data science capacity
  • Share knowledge and expertise
  • Establish best practices and standards
  • Ensure participation by provincial and territorial groups
  • Ensure participation of academic institutions and international partners
  • Use resource more efficiently and effectively.

2020-2021 Objectives for the Data Science Network

  • Connect with departments and communities of practice to make information available to community members.
  • Build data science learning resources to catalog needs and share opportunities.
  • Start building data scientist career paths to lay the groundwork for standardized job descriptions.

The next portion of the presentation focused on the governance and sustainability plan and included a discussion of the funding model and the plan to schedule regular directors' committee meetings. A draft copy of the Network's Terms of Reference was also provided to participants, which outlines the committee's membership and mandate.

This was followed by a lively discussion about the Network's five areas of focus:

  • Talent management—Participants discussed the importance of aligning competencies for data scientists across the public service.
  • Training and learning—Participants shared information on how training is done in their departments and discussed ideas for sharing data science resources and the need for continued engagement with existing data literacy efforts.
  • Information sharing—Participants discussed plans for sharing information within the Steering Committee.
  • Collaboration—The Data Science Network established a GCwiki page for all members to facilitate collaboration.
  • Joint services—Offering services to other departments was seen as a potential future area of opportunity.

The Data Science Network's five areas of focus

Talent management

  • development program
  • career paths
  • hiring pools
  • interview protocol
  • responsibility differentiation

Training and learning

  • generic job description
  • vetted courses and events
  • certification standards
  • best practices

Information sharing

  • info hub
  • departmental champions
  • tools repository
  • discussion channels
  • connection point for DS

Collaboration

  • code sharing
  • data sharing
  • help services
  • standard licensing
  • coding best practices

Joint services

  • cost recovery
  • help for business needs
  • software toolbox
  • common platforms
  • rapid infrastructure

The meeting ended with a discussion about the upcoming 2021 Data Conference and how the Network could contribute to this important event (including leading panels and workshops).

The members were eager to discuss next steps, and have already begun to share resources and ideas.

The group looks forward to reconvening in March 2021 and continuing to work together to advance data science in the Government of Canada and beyond. For more information on how your organization can get involved in the Data Science Network, please email statcan.dsnfps-rsdfpf.statcan@statcan.gc.ca.

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A Brief Survey of Privacy Preserving Technologies

By: Zachary Zanussi, Statistics Canada

As an organization, StatCan has always strived to adopt new technologies in a timely manner and innovate with methods. Big data technologies such as deep learning have increased the utility of data exponentially, and cloud computing has been an enabling vehicle for this, in particular when working with unclassified data. However, computations of unencrypted sensitive data in a cloud environment may provide exposure to confidentiality threats and cyber-security attacks. Statistics Canada has strict privacy policy measures that have been developed over decades of collecting data and releasing official statistics. To address the new requirements for operating in the cloud, we consider a class of new cryptographic techniques called Privacy Preserving Technologies (PPTs) that might help increase utility by taking greater advantage of technologies such as the cloud or machine learning while continuing to preserve the agency's security posture. This post provides a brief introduction to a number of these PPTs.

Description - Figure 1 Enhancing utility within the privacy vs. utility equation. The red solid line shows the privacy-utility balance with traditional methods, while the green dotted line shows what we hope to achieve with new privacy preserving technologies.

What do we mean by privacy? Privacy is the right of individuals to control or influence what information related to them may be collected, used and stored and by whom, and to whom that information may be disclosed. As Canada's national statistical organization, most of the data used at Statistics Canada are provided by respondents, such as an individual or a business. The confidentiality of the data is safeguarded according to the five safe principles to protect the privacy of these respondents by ensuring that the data they provide can't be traced back to them directly or from statistical outputs. More information on Statistics Canada's approach to privacy can be found in the Statistics Canada Trust Centre.

A breach of information involves an attacker successfully reidentifying a response and attributing it back to a particular respondent; in the case that the respondent is a person, then it is also called a breach of privacy. In this article, we will mainly use the terminology of privacy, while keeping in mind that these technologies, applied correctly, protect the data of any kind of respondent.

The respondents' data are considered as the input to some statistical process that produces an output. If an attacker gains access to the input data, then it's a breach of input privacy, while if the attacker can reverse engineer private data from the output, then it's a breach of output privacy. It is possible to prevent both of these types of breaches using classical statistical methods such as anonymizing, where potentially attributing features of data are removed; or perturbation, where the data values are modified in some way to prevent accurate reidentification. The downside is that these classical methods necessarily sacrifice the utility of the data, in particular sensitive data. Moreover, there are numerous reidentification examples which prove that these traditional techniques do not necessarily provide desired cryptographic security guaranteesNote de bas de page 1, Note de bas de page 2. The goal is to leverage PPTs to maintain strong privacy attributes while preserving as much utility as possible. The end result is effectively enhancing utility in the privacy vs. utility equation.

Differential privacy to preserve output privacy

Description - Figure 2 In differential privacy, the outputs of an algorithm on very similar datasets should be within some agreed-upon value known as epsilon. Here, the addition of the central (magenta) respondent changes the output of ƒ by an amount that is bounded by ε.

The output privacy of respondents is protected by carefully controlling the results of aggregate statistics. For example, it's possible for an adversary to reconstruct input data through the careful analysis of published statistics. Alternatively, if the public has query access to a secure database, where someone could request simple statistics (mean, max, min, etc.) on subsets of the database, an adversary could abuse this system to extract input data. Differential privacy reduces this risk through the addition of noise to input or output data. At first glance, this is simply an example of the data perturbation that has been employed in official statistics for decades. The innovation is the rigorous mathematical formulation of differential privacy, allowing to precisely gauge exactly where on the "Privacy—Utility" scale an algorithm resides using a parameter ε, called "epsilon."

An algorithm is called ε-differentially private if running the algorithm on two databases that differ by exactly one entry produces results that differ by less than ε. Informally, this means that an adversary querying the same statistic from differing subsets of a database can only infer an amount of information from the database that is bounded by ε. In practice, before releasing statistics, the level of privacy required is determined and used to set ε. Then, random noise is added to the data until the algorithms or statistics to be computed are ε-differentially private. Using differential privacy, better guarantees output privacy while maximizing utility.

Private computation as a means of protecting input privacy

Private computation is a blanket term covering a number of different frameworks for computing on data securely. For example, suppose you hold private data that you'd like to perform some sort of computation on, but you don't have access to a secure computing environment—you might be interested in homomorphic encryption. Or suppose you and several peers would like to perform a shared computation on your data without sharing it amongst yourselves—secure multiparty computation might be just what you are looking for. These two secure computing paradigms will be examined in more detail below.

With recent advances in cloud computing, individuals and organizations have unprecedented access to powerful and affordable cloud computing environments. However, most cloud providers do not guarantee the security of data while they are being processed, which means that the cloud is still out of reach to many organizations in possession of highly sensitive private data. Homomorphic encryption (HE) can change this. While traditional encryption algorithms require data to be decrypted before and after use (encryption-at-rest), in HE computations can be performed directly on encrypted data. The results of the computation can only be revealed after decryption. Thus, a data holder can encrypt their data and send them to the cloud knowing that it is cryptographically protected. The cloud can perform the desired computation homomorphically and return the encrypted result, which only the data holder can decrypt and view. In this way, the client can delegate its computations to the cloud without having to rely on trust that their data will be protected; it is secured by encryption! The downside of HE is increased computational complexity, which can be orders of magnitude larger than the corresponding unencrypted computation.

Suppose a number of hospitals have data about patients with a rare disease. If they pool their data, they could run some computations that would help them with treatment and prevention strategies. Laws in many countries require medical institutions to protect their patients' medical data. In the past, the only solution to this problem would be to have all the hospitals agree on a single trusted authority who would collect the data and run the computation. Today, the hospitals could implement (secure) multiparty computation (MPC). With MPC, the hospitals can collaborate and jointly perform their computations without sharing their input data with any party, dispensing the need for a trusted authority, in such a way that their input privacy is guaranteed even in the face of "dishonest" hospitals. MPC protocols are usually implemented using multiple rounds of "secret sharing," where each party holds a piece of a smaller computation that they use to perform their larger computation. The downside of MPC is increased computational complexity (although, usually not as much as HE) and the fact that the protocols usually entail multiple rounds of interactive communication.

Distributed learning

Neural networks and artificial intelligence may be the two technologies that have thrived the most in the era of big data. Rather than write a program to complete a task, data are fed into a machine and it trains a model to perform the task. This makes data collection the most important part of the process. As discussed above, this collection process can be prohibitive when the data are distributed and sensitive. Distributed learning is a class of MPC protocols that aim to train a model on data that is owned by multiple parties who want to keep their data private. Two protocols that implement this process in slightly different ways, known as Federated Learning and Split Learning will be discussed. The remainder of this section will assume a basic knowledge of how to train a neural network.

Both of these protocols begin with the same setup; multiple parties have access to data that they consider sensitive, and there is a central untrusted authority server who will assist them. The parties agree on a neural network architecture they would like to train, as well as other particulars such as hyperparameters. Here the two ideas diverge.

Description - Figure 3 In federated learning, each data holder computes gradients ∇ ₓ on their data and sends it up to a central authority who computes ∇ and distributes it down to each party. In this way, each party can obtain a neural network that has been trained on the union of their datasets, without sharing their data.

In federated learning, each party holds an identical local copy of the network they are training. They each perform one epoch of training on their network and send their gradients to the authority. The authority coordinates these gradients and instructs each of the parties on how to update their local models by combining the insights gained by every party's data. The process then repeats for the desired number of epochs, where finally the authority and every party holds a trained version of the network that they can use however they see fit. The resulting networks are identical, and the process reveals no more about the data than the accumulated gradients computed by each party. This could potentially facilitate an avenue for attack that needs to be considered when implementing a federated learning scheme.

Description - Figure 4 In split learning, the desired network is "split" between the parties and the server. Forward propagation is shown going up in dark blue, and backward propagation goes down in magenta. Each party performs forward propagation up to the split and sends the result to the server, who propagates forward and back again, sending the gradients back to their respective parties who can then update their networks.

In split learning, the neural net is split by the authority at a certain layer, and layers after the split are shared with the parties. Each party propagates their data up to the cut, then sends the activations at the cut layer to the server. The server finishes the forward propagation on the rest of the network, performs backward propagation up to the cut, then sends the gradients to the parties who can then each finish back propagation and update their copy of the network. After the desired number of epochs, the authority distributes its half of the network to each of the parties, and then each party has their own copy of the total network, the bottom half of each being explicitly tailored to their data. The only data leaked are those which can be inferred from the activations and gradients exchanged at each epoch. The layers below the split serve to alter the data enough that they are protected (sometimes called "smashing" the data), while still allowing the server to gather insights from it.

This article discussed a number of emerging privacy preserving technologies and how they can improve the utility extracted from data without sacrificing the privacy of those providing it. Future posts will take a more in-depth look at some of these technologies, so stay tuned! Next up is a much closer look at homomorphic encryption, from the mathematics of lattices to applications.

Want to keep in the loop about these emerging technologies, or want to share your work in the field of privacy? Check out our Privacy Preserving Technologies Community of Practice GCConnex page to discuss these DSN privacy posts, connect with peers interested in privacy, and share resources and ideas with the community. You can also give feedback on this post or leave suggestions for future posts in this series.

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Future-Oriented Statement of Operations
March 31, 2022

Future-Oriented Statement of Operations (unaudited)
for the year ending March 31
(in thousands of dollars)
  Forecast results 2020-21 Planned results 2021-22
Expenses
Statistical information
 773,547 977,075
Internal services
 94,092 71,099
Total expenses 867,639 1,048,174
Revenues
Special statistical services
 129,403 138,000
Other revenues
 100 100
Revenues earned on behalf of the Government of Canada
 -16,346 -18,100
Total revenues 113,157 120,000
Net cost of operations before government funding and transfers 754,482 928,174

The accompanying notes form an integral part of the Future-Oriented Statement of Operations

Notes to the Future-Oriented Statement of Operations (unaudited) for the year ending March 31

1. Methodology and significant assumptions

The Future-Oriented Statement of Operations has been prepared on the basis of government priorities and the plans of Statistics Canada (the agency) as described in the 2021-22 Departmental Plan.

The information in the forecasted results for fiscal year 2020-21 is based on actual results as at December 30, 2020 and on forecasts for the remainder of the fiscal year. Forecasts were estimated for the planned results for fiscal year 2021-22.

The main assumptions underlying the forecasts are as follows:

  • The agency's activities will remain substantially the same as the previous year.
  • Expenses and revenues, including the determination of amounts internal and external to the government, are based on historical trends and known cyclical changes.

These assumptions are made as at December 30, 2020.

2. Variations and changes to the forecast financial information

Although every attempt has been made to forecast final results for the remainder of 2020-21 and for 2021-22, actual results achieved for both years are likely to differ from the forecasted information presented, and this variation could be material.

In preparing this Future-Oriented Statement of Operations, the agency established estimates and assumptions about the future. These estimates and assumptions may differ from the subsequent actual results. Estimates and assumptions are based on past experience and other factors, including expectations of future events that are believed to be reasonable under the circumstances, and are continually evaluated.

Factors that could lead to material differences between the Future-Oriented Statement of Operations and the historical financial statements include:

  • the timing and the amount of acquisitions and disposals of property which may affect gains, losses and amortization expenses;
  • the implementation of new collective agreements;
  • economic conditions, which may affect both the amount of revenue earned and the collectability of receivables; and
  • other changes to the operating budget, such as new initiatives or technical adjustments made later in the fiscal year.

After the Departmental Plan is tabled in Parliament, the agency will not be updating the forecasts for any changes in financial resources made in ensuing supplementary estimates. Variances will be explained in the Departmental Results Report.

3. Summary of significant accounting policies

The Future-Oriented Statement of Operations has been prepared using the Government of Canada's accounting policies in effect for fiscal year 2020-21, and is based on Canadian public sector accounting standards. The presentation and results using the stated accounting policies do not result in any significant differences from Canadian public sector accounting standards.

Significant accounting policies are as follows:

(a) Expenses

Transfer payments are recorded as an expense in the year the transfer is authorized and all eligibility criteria have been met by the recipient.

Other expenses are generally recorded when goods are received or services are rendered and include expenses related to personnel, professional and special services, repair and maintenance, utilities, materials and supplies, as well as amortization of tangible capital assets. Provisions to reflect changes in the value of assets or liabilities, such as provisions for bad debts, advances and inventory obsolescence, as well as utilization of inventories and prepaid expenses, and other are also included in other expenses.

(b) Revenues

Funds received for special statistical services are recorded upon receipt as deferred revenue. These revenues are recognized in the period in which the related expenses are incurred.

Deferred revenue consists of amounts received in advance of the delivery of goods and rendering of services that will be recognized as revenue in a subsequent fiscal year as it is earned.

Other revenues are recognized in the period the event giving rise to the revenues occurred.

Revenues that are non-respendable are not available to discharge the agency's liabilities. Although the deputy head is expected to maintain accounting control, he has no authority over the disposition of non-respendable revenues. As a result, non-respendable revenues are considered to be earned on behalf of the Government of Canada and are therefore presented as a reduction of the agency's gross revenues.

4. Parliamentary authorities

The agency is financed in part by the Government of Canada through parliamentary authorities. Financial reporting of authorities provided to the agency differs from financial reporting according to generally accepted accounting principles because authorities are based mainly on cash flow requirements. Items recognized in the Future-Oriented Statement of Operations in one year may be funded through parliamentary authorities in prior, current or future years. Accordingly, the agency has a different net cost of operations for the year on a government funding basis than on an accrual accounting basis. The differences are reconciled in the following tables:

(a) Reconciliation of net cost of operations to requested authorities (in thousands of dollars)

Reconciliation of net cost of operations to requested authorities (in thousands of dollars)
  Forecast results 2020-21 Planned results 2021-22
Net cost of operations before government funding and transfers 754,482 928,174
Adjustments for items affecting net cost of operations but not affecting authorities:
Amortization of tangible capital assets
 -28,106 -24,975
Loss on disposal of tangible capital assets
 -56 0
Services provided without charge by other federal government departments
 -107,298 -108,584
Increase/decrease in vacation pay and compensatory leave
 -17,708 7,014
Increase in employee future benefits
 -906 -1,847
Refunds of previous years expenditures
 712 712
Consumption of prepaid expenses
 -13,181 -12,061
Bad debt expense
 -3 0
Accrued salary receivables
 187 0
Total items affecting net cost of operations but not affecting authorities
 -166,359 -139,741
Adjustments for items not affecting net cost of operations but affecting authorities:
Acquisitions of tangible capital assets
 30,863 29,266
Increase in prepaid expenses
 12,795 13,261
Transfer of payment in arrears
 5 0
Payments for pay equity settlement
 140 140
Total items not affecting net cost of operations but affecting authorities
 43,803 42,667
Requested authorities forecasted to be used 631,926 831,100

(b) Authorities requested (in thousands of dollars)

Authorities requested (in thousands of dollars)
  Forecast results 2020-21 Planned results 2021-22
Authorities requested
Vote 1: operating expenditures
 586,646 748,327
Statutory amounts
 79,842 82,773
Total authorities requested 666,488 831,100
Less: Estimated unused authorities and other adjustments
 -34,562 0
Requested authorities forecasted to be used 631,926 831,100

2021 Census: 3A

Message from the Chief Statistician of Canada

Thank you for taking a few minutes to participate in the 2021 Census. The information you provide is converted into statistics used by communities, businesses and governments to plan services and make informed decisions about employment, education, health care, market development and more.

Your answers are collected under the authority of the Statistics Act and kept strictly confidential. By law, every person must complete a 2021 Census of Population questionnaire.

Statistics Canada makes use of existing sources of information such as immigration, income tax and benefits data to ensure the least amount of burden is placed on households.

The information that you provide may be used by Statistics Canada for other statistical and research purposes or may be combined with other survey or administrative data sources.

Make sure you count yourself into Canada's statistical portrait, and complete your census questionnaire today.

Thank you,

Anil Arora
Chief Statistician of Canada

Complete your census questionnaire:

  • Please print using CAPITAL LETTERS.
  • Mark circles with "X".

Any questions?

  • www.census.gc.ca
  • Call us free of charge at 1-855-340-2021
  • TTY: 1-833-830-3109

Français au verso

Confidential when completed

This information is collected under the authority of the Statistics Act, R.S.C. 1985, c. S-19.

Step A

1. What is your telephone number?

  • Number, Ext.

2. What is the address where you received this questionnaire?

  • Number (and suffix, if applicable)
    (e.g., 302, 151 B, 16 1/2)
  • Street name, street type (e.g., DR = Drive), direction (e.g., N = North)
  • Apartment/unit/room
  • City, municipality, town, village, Indian reserve
  • Province/territory
  • Postal code

3. What is the mailing address of this dwelling, if different from above?
(e.g., Rural Route, PO Box, General Delivery)

Step B

1. What is your name?

  • Family name(s)
  • Given name(s)

Step C

The following questions refer to your situation on May 11, 2021.

If you are:

  • a Canadian citizen
    • Continue with step D
  • a landed immigrant (permanent resident)
    • Continue with step D
  • a person who has claimed refugee status (asylum seeker) in Canada
    • Continue with step D
  • a person from another country with a work or study permit
    • Continue with step D

If you are:

  • a resident of another country visiting Canada, for example, on vacation or on a business trip
    • Mark "X" the circle
      STOP HERE and see instructions in Step E on page 6.
  • a government representative of another country
    • Mark "X" the circle
      STOP HERE and see instructions in Step E on page 6.

Step D

Is this your main residence?

  • Yes
    • Continue with question 1 a) on the next page
  • No, but I have no other residence in Canada
    • Continue with question 1 a) on the next page
  • No, it is somewhere else in Canada
    • Specify complete address
      • Number (and suffix, if applicable)
        (e.g., 302, 151 B, 16 1/2)
      • Street name, street type (e.g., DR = Drive), direction (e.g., N = North)
      • Apartment/unit/room
      • City, municipality, town, village, Indian reserve
      • Province/territory
      • Postal code
      • Telephone number

      STOP HERE.
      You should be included on the household questionnaire for the above address.
      See instructions in Step E on page 6.

1. a) Is there any other address in Canada where someone may include you on the census form for that household?

    For example, at the home of a parent, relative or friend, or a place where you live while working, or a vacation home.

    • No
      • Go to question 2
    • Yes
      • Specify complete address
        • Number (and suffix, if applicable)
          (e.g., 302, 151 B, 16 1/2)
        • Street name, street type (e.g., DR = Drive), direction (e.g., N = North)
        • Apartment/unit
        • City, municipality, town, village, Indian reserve
        • Province/territory
        • Postal code
        • Telephone number

    1. b) Please give the name of another adult (if any) living at this other address.

    • Family name(s)
    • Given name(s)
    • No other adult

    2. What was your sex at birth?

    Sex refers to sex assigned at birth.

    • Male
    • Female

    3. What is your gender?

    Refers to current gender which may be different from sex assigned at birth and may be different from what is indicated on legal documents.

    • Male
    • Female
    • Or please specify your gender:

    4. What are your date of birth and age?

    If exact date of birth is not known, enter best estimate. For children less than 1 year old, enter 0 for age.

    • Day
    • Month
    • Year
    • Age

    5. What is your marital status?

    Mark "x" one circle only.

    • Never legally married
    • Legally married (and not separated)
    • Separated, but still legally married
    • Divorced
    • Widowed

    6. Are you living with a common-law partner?

    Common-law refers to two people who live together as a couple but who are not married, regardless of the duration of the relationship.

    • Yes
    • No

    7. What is your status here (at the address you entered on the front cover)?

    Mark “x” or specify one response only.

    • Resident under care or custody (e.g., patient, inmate)
    • Roommate, lodger or boarder
    • Employee
    • Employee’s family member
    • Other status — specify:

    8. Can you speak English or French well enough to conduct a conversation?

    Mark "x" one circle only.

    • English only
    • French only
    • Both English and French
    • Neither English nor French

    9. a) What language(s) do you speak on a regular basis at home?

    • English
    • French
    • Other language(s) — specify:

    If you indicate only one language in question 9. a), go to question 10.

    9. b) Of these languages, which one do you speak most often at home?

    Indicate more than one language only if they are spoken equally at home.

    • English
    • French
    • Other language — specify:

    10. What is the language that you first learned at home in childhood and still understand?

    If you no longer understand the first language learned, indicate the second language learned.

    • English
    • French
    • Other language — specify:

    11. Have you ever served in the Canadian military?

    Canadian military service includes service with the Regular Force or Primary Reserve Force as an Officer or Non-Commissioned Member. It does not include service with the Cadets (COATS), the Supplementary Reserve or the Canadian Rangers.

    Mark "x" one circle only.

    • Yes, currently serving in the Regular Force or the Primary Reserve Force
    • Yes, but no longer serving in the Regular Force or the Primary Reserve Force
    • No

    The following questions collect information in accordance with the Canadian Charter of Rights and Freedoms to support education programs in English and French in Canada.

    12. Is this dwelling located in Quebec?

    • No
      • Continue with question 13.
    • Yes
      • Go to question 16.

    13. Did you do any of your primary or secondary schooling in French in Canada (including immersion)?

    Mark "x" one circle only.

    • Yes (previously or currently attending)
    • No
      • Go to Step E

    14. In which type of program was this schooling in French done?

    • A regular French program in a French-language school
    • A French immersion program in an English-language school
      • Go to Step E
    • Both types of programs
    • Other program — specify:

    15. For how many years did you attend a regular French program in a French-language school?

    • Number of years in primary schooling (including kindergarten and middle school)
      • Number of years
        • Go to Step E
    • Number of years in secondary schooling
      • Number of years
        • Go to Step E

    16. Did you do any of your primary or secondary schooling in an English-language school in Canada (including immersion)?

    Mark "x" one circle only.

    • Yes (previously or currently attending)
    • No
      • Go to Step E

    17. For how many years did you do your schooling in an English-language school in Canada (including immersion)?

    • Number of years in primary schooling (including kindergarten)
      • Number of years
    • Number of years in secondary schooling
      • Number of years

    Step E

    You have now completed your questionnaire.

    Please see instructions on the envelope.

    Thank you for your cooperation.

      The law protects what you tell us

      The confidentiality of your responses is protected by law. All Statistics Canada employees have taken an oath of secrecy. Your personal information cannot be given to anyone outside Statistics Canada without your consent. This is your right.

      Reasons why we ask the questions

      Steps A to D and question 1 are used to collect contact information and determine who should be included on the questionnaire. They help us ensure that we have counted everyone we need to count and that no one is counted twice.

      Questions 2 to 7 provide information about the living arrangements of people in Canada, the family size, the number of children living with one parent or two parents, and the number of people who live alone. This information is used for planning social programs, such as Old Age Security and the Canada Child Benefit. It is also used by municipalities to plan a variety of services such as day care centres, schools, police, fire protection and residences for seniors.

      Questions 8 to 10 are used to provide a profile of the linguistic diversity of Canada's population. This information is used to estimate the need for services in English and French, and to better understand the current state and the evolution of Canada's various language groups.

      Question 11 provides information on the number of people with Canadian military experience. Governments will use this information to develop programs and services to meet the changing needs of the Veteran population.

      Questions 12 to 17 collect information in accordance with the Canadian Charter of Rights and Freedoms to support education programs in English and French in Canada.

      Comments

      Please use the space provided below if you have concerns, suggestions or comments to make about:

      • the steps to follow or the content of this questionnaire (for example, a question that was difficult to understand or to answer)
      • the characteristics of the questionnaire (for example, the design, the format, the size of the text).

      2021 Census: 2C

      Message from the Chief Statistician of Canada

      Thank you for taking a few minutes to participate in the 2021 Census. The information you provide is converted into statistics used by communities, businesses and governments to plan services and make informed decisions about employment, education, health care, market development and more.

      Your answers are collected under the authority of the Statistics Act and kept strictly confidential. By law, every person must complete a 2021 Census of Population questionnaire.

      Statistics Canada makes use of existing sources of information such as immigration, income tax and benefits data to ensure the least amount of burden is placed on households.

      The information that you provide may be used by Statistics Canada for other statistical and research purposes or may be combined with other survey or administrative data sources.

      To ensure confidentiality, put your completed questionnaire in the envelope provided and seal it. Return the envelope in accordance with the instructions given by your unit or department. Only Statistics Canada staff will open the envelopes.

      Make sure you count yourself into Canada's statistical portrait, and complete your census questionnaire today.

      Thank you,

      Anil Arora
      Chief Statistician of Canada

      Any questions?

      Visit www.census.gc.ca

      Ce questionnaire est disponible en français

      • Please print using CAPITAL LETTERS.
      • Mark circles with an "X".

      Confidential when completed

      This information is collected under the authority of the Statistics Act, R.S.C. 1985, c. S-19.

      Step A

      1. Do you have a permanent place of residence in Canada presently occupied by one or more members of your family?

      • Yes
        • What is the address of your permanent place of residence?
          • Number (and suffix, if applicable)
            (e.g., 302, 151 B, 16 1/2)
          • Street name, street type (e.g., DR = Drive), direction (e.g., N = North)
          • Apartment/unit
          • City, municipality, town, village, Indian reserve
          • Province/territory
          • Postal code
          • Telephone number
          • Enter the name of an adult living at this address.
            • Family name(s)
            • Given names(s)
      • No
        • What is the address you give for election purposes?
          If you have no such address, enter your last permanent address in Canada.
          • Number (and suffix, if applicable)
            (e.g., 302, 151 B, 16 1/2)
          • Street name, street type (e.g., DR = Drive), direction (e.g., N = North)
          • Apartment/unit
          • City, municipality, town, village, Indian reserve
          • Province/territory
          • Postal code
          • Telephone number

      2. Enter the name and address of the military or government establishment outside Canada to which you are presently attached or, if none, the city or town and the country in which you reside.

      • Name of establishment
      • Location — City or town
      • Country

      Step B

      1. Including yourself, how many persons usually live at your address (outside Canada) as of May 11, 2021?

      Include: all persons who have their main residence at this address, even if they are temporarily away, provided they are:

      • Canadian government employees (federal, provincial and territorial) or a member of their family OR members of the Canadian Armed Forces or a member of their family who are stationed outside Canada,
      • other Canadian citizens OR persons with Canadian landed immigrant status who are outside Canada on Census Day, but whose permanent residence is in Canada.
      • Number of persons

      2. Including yourself, list all persons who usually live at your address (outside Canada).

      Important: Begin the list with an adult followed, if applicable, by that person's spouse or common-law partner and by their children. Continue with all other persons who usually live at this address.

      • Person 1: Family name(s), Given name(s)
      • Person 2: Family name(s), Given name(s)
      • Person 3: Family name(s), Given name(s)
      • Person 4: Family name(s), Given name(s)
      • Person 5: Family name(s), Given name(s)
      • Person 6: Family name(s), Given name(s)
      • Person 7: Family name(s), Given name(s)
      • Person 8: Family name(s), Given name(s)
      • Person 9: Family name(s), Given name(s)
      • Person 10: Family name(s), Given name(s)

      Step C

      Copy the names in Step B to question 1, at the top of page 4.

      Keep the same order.

      If more than six persons live at your address (outside Canada), you will need an extra questionnaire. A second questionnaire may be obtained from the representative or official who delivered this one.

      1. Name

      In the spaces provided, copy the names in the same order as in Step B. Then answer the following questions for each person.

      Person 1

      • Family name
      • Given name

      The following questions refer to each person's situation on May 11, 2021, unless otherwise specified.

      2. What was this person's sex at birth?

      Sex refers to sex assigned at birth.

      • Male
      • Female

      3. What is this person's gender?

      Refers to current gender which may be different from sex assigned at birth and may be different from what is indicated on legal documents.

      • Male
      • Female
      • Or please specify this person's gender:

      4. What are this person's date of birth and age?

      If exact date of birth is not known, enter best estimate. For children less than 1 year old, enter 0 for age.

      • Day
      • Month
      • Year
      • Age

      5. What is this person's marital status?

      Mark "x" one circle only.

      • Never legally married
      • Legally married (and not separated)
      • Separated, but still legally married
      • Divorced
      • Widowed

      6. Is this person living with a common-law partner?

      Common-law refers to two people who live together as a couple but who are not married, regardless of the duration of the relationship.

      • Yes
      • No

      7. What is the relationship of this person to Person 1?

      If none of the responses in the list describes this person's relationship to Person 1, then specify a response under "Other relationship".

      Person 1

      • Person 1

      Person 2

      • Husband or wife of Person 1
      • Common-law partner of Person 1
      • Son or daughter of Person 1 only
      • Grandchild of Person 1
      • Son-in-law or daughter-in-law of Person 1
      • Father or mother of Person 1
      • Father-in-law or mother-in-law of Person 1
      • Brother or sister of Person 1
      • Foster child
      • Roommate, lodger or boarder
      • Other relationship — specify:

      Persons 3-6

      • Son or daughter of both Persons 1 and 2
      • Son or daughter of Person 1 only
      • Son or daughter of Person 2 only
      • Grandchild of Person 1
      • Son-in-law or daughter-in-law of Person 1
      • Father or mother of Person 1
      • Father-in-law or mother-in-law of Person 1
      • Brother or sister of Person 1
      • Foster child
      • Roommate, lodger or boarder
      • Other relationship — specify:

      8. Can this person speak English or French well enough to conduct a conversation?

      Mark "x" one circle only.

      • English only
      • French only
      • Both English and French
      • Neither English nor French

      9. a) What language(s) does this person speak on a regular basis at home?

      • English
      • French
      • Other language(s) — specify:

      If this person indicates only one language in question 9. a), go to question 10.

      9. b) Of these languages, which one does this person speak most often at home?

      Indicate more than one language only if they are spoken equally at home.

      • English
      • French
      • Other language — specify:

      10. What is the language that this person first learned at home in childhood and still understands?

      If this person no longer understands the first language learned, indicate the second language learned.

      • English
      • French
      • Other language — specify:

      11. Has this person ever served in the Canadian military?

      Canadian military service includes service with the Regular Force or Primary Reserve Force as an Officer or Non-Commissioned Member. It does not include service with the Cadets (COATS), the Supplementary Reserve or the Canadian Rangers.

      Mark "x" one circle only.

      • Yes, currently serving in the Regular Force or the Primary Reserve Force
      • Yes, but no longer serving in the Regular Force or the Primary Reserve Force
      • No

      The following questions collect information in accordance with the Canadian Charter of Rights and Freedoms to support education programs in English and French in Canada.

      12. Is the address in Canada you provided in Step A, question 1, located in Quebec?

      • No
        • Continue with question 13.
      • Yes
        • Go to question 16.

      13. Did this person do any of their primary or secondary schooling in French in Canada (including immersion)?

      Mark "x" one circle only.

      • Yes (previously or currently attending)
      • No
        • Go to Step D

      14. In which type of program was this schooling in French done?

      • A regular French program in a French-language school
      • A French immersion program in an English-language school
        • Go to Step D
      • Both types of programs
      • Other program — specify:

      15. For how many years did this person attend a regular French program in a French-language school?

      • Number of years in primary schooling (including kindergarten and middle school)
        • Number of years
          • Go to Step D
      • Number of years in secondary schooling
        • Number of years
          • Go to Step D

      16. Did this person do any of their primary or secondary schooling in an English-language school in Canada (including immersion)?

      Mark "x" one circle only.

      • Yes (previously or currently attending)
      • No
        • Go to Step D

      17. For how many years did this person do their schooling in an English-language school in Canada (including immersion)?

      • Number of years in primary schooling (including kindergarten)
        • Number of years
      • Number of years in secondary schooling
        • Number of years

      Step D

      Comments

      Please use the space provided below if you have concerns, suggestions or comments to make about:

      • the steps to follow or the content of this questionnaire (for example, a question that was difficult to understand or to answer)
      • the characteristics of the questionnaire (for example, the design, the format, the size of the text).

      Step E

      If more than six persons live at your address (outside Canada), you will need an extra questionnaire. A second questionnaire may be obtained from the representative or official who delivered this one.

      You have now completed your questionnaire. Please return it in accordance with instructions from your unit or department.

      Thank you for your cooperation.

      Reasons why we ask the questions

      Steps A and B and question 1 are used to collect contact information and determine who should be included on the questionnaire. They help us ensure that we have counted everyone we need to count and that no one is counted twice.

      Questions 2 to 7 provide information about the living arrangements of people in Canada, the family size, the number of children living with one parent or two parents, and the number of people who live alone. This information is used for planning social programs, such as Old Age Security and the Canada Child Benefit. It is also used by municipalities to plan a variety of services such as day care centres, schools, police, fire protection and residences for seniors.

      Questions 8 to 10 are used to provide a profile of the linguistic diversity of Canada's population. This information is used to estimate the need for services in English and French, and to better understand the current state and the evolution of Canada's various language groups.

      Question 11 provides information on the number of people with Canadian military experience. Governments will use this information to develop programs and services to meet the changing needs of the Veteran population.

      Questions 12 to 17 collect information in accordance with the Canadian Charter of Rights and Freedoms to support education programs in English and French in Canada.

        The law protects what you tell us

        The confidentiality of your responses is protected by law. All Statistics Canada employees have taken an oath of secrecy. Your personal information cannot be given to anyone outside Statistics Canada without your consent. This is your right.

        Canadian COVID-19 Antibody and Health Survey (CCAHS) - Privacy impact assessment summary

        Introduction

        Statistics Canada is conducting the Canadian COVID-19 Antibody and Health Survey (CCAHS) from November 2020 to March 2021. This survey collects health data on the current COVID-19 pandemic by asking selected participants to complete an electronic questionnaire and provide a blood sample from a self-administered finger prick (dried blood spot sample). This voluntary survey will be sent to approximately 48,000 Canadians, aged 1 and over, across the provinces and territories. It is expected that approximately 20,000 respondents will complete the entire survey (questionnaire and blood sample).

        All processes of the CCAHS have been reviewed and approved by the Health Canada/Public Health Agency of Canada Research Ethics Board to ensure that internationally recognized ethical standards for human research are met and maintained.

        Objective

        A privacy impact assessment for the CCAHS was conducted to determine if there were any privacy, confidentiality or security issues with this survey and to make recommendations to resolve or mitigate any issues.

        Description

        This survey was developed in consultation with the COVID-19 Immunity Task Force (CITF). The CITF is funded by the Government of Canada and is composed of members from various domains, including universities, hospitals and the public health sector. The CITF was created to support the development and implementation of population-based serological studies (using blood tests) on the SARS-CoV-2 virus in order to better understand the impact of the pandemic in Canada.

        Results from this survey will provide important information on the health status of Canadians during the COVID-19 pandemic, including an estimate of the prevalence of infection from SARS-CoV-2, the virus that causes COVID-19. This survey will also provide a platform to explore new measurement techniques, as this is the first time that self-administered blood samples are being collected from a nationally-representative sample of Canadians.

        Risk Area Identification and Categorization

        The PIA identifies the level of potential risk (level 1 is the lowest level of potential risk and level 4 is the highest) associated with the following risk areas:

        Risk Area Identification and Categorization
          Risk scale

        a) Type of program or activity

        Program or activity that does not involve a decision about an identifiable individual.

        		 1

        b) Type of personal information involved and context

        Sensitive personal information, including detailed profiles, allegations or suspicions and bodily samples, or the context surrounding the personal information is particularly sensitive.

        		 4

        c) Program or activity partners and private sector involvement

        Private sector organizations, international organizations or foreign governments

        		 4

        d) Duration of the program or activity

        One-time program or activity

        		 1

        e) Program population

        The program's use of personal information is not for administrative purposes. Information is collected for statistical purposes, under the authority of the Statistics Act.

        		 N/A

        f) Personal information transmission

        The personal information is transmitted using wireless technologies.

        		 4

        g) Technology and privacy

        The CCAHS does not require the implementation of new technology or modifications to legacy systems to support the creation, collection or handling of personal information.

        h) Potential risk that in the event of a privacy breach, there will be an impact on the individual or employee.

        There is a very low risk for a breach of any personal information being disclosed without proper authorization. The impact on the individual would be high, as it could negatively affect their reputation because of the stigmatization related to certain health conditions or illnesses.

        Conclusion

        This assessment of the CCAHS did not identify any privacy risks that cannot be managed using existing Statistics Canada safeguards and procedures, as well as those in place at the various laboratories being used. Any remaining risks are either negligible or are such that Statistics Canada is prepared to accept and manage.

        CVs for operating revenue - Food services and drinking places - 2019

        CVs for operating revenue - Food services and drinking places - 2019
        Geography CVs for operating revenue
        percent
        Canada 0.32
        Newfoundland and Labrador 1.43
        Prince Edward Island 0.45
        Nova Scotia 0.26
        New Brunswick 1.14
        Quebec 0.80
        Ontario 0.45
        Manitoba 1.16
        Saskatchewan 0.79
        Alberta 0.62
        British Columbia 0.63
        Yukon 0.88
        Northwest Territories 0.00
        Nunavut 0.00

        Employment services - CVs for operating revenue - 2019

        CVs for operating revenue - Employment services - 2019
        Geography CVs for operating revenue
        percent
        Canada 0.00
        Newfoundland and Labrador 0.00
        Prince Edward Island 0.00
        Nova Scotia 0.00
        New Brunswick 0.00
        Quebec 0.01
        Ontario 0.00
        Manitoba 0.00
        Saskatchewan 0.00
        Alberta 0.01
        British Columbia 0.00
        Yukon 0.00
        Northwest Territories 0.06
        Nunavut 0.00
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