Table of contents

• Message from the Canadian Statistics Advisory Council
• Executive summary
• 1. Introduction
• 2. National data strategy
  • 2.1. Critical data gaps
    • Data gaps on health and health care
    • Data gaps on racialized groups and Indigenous peoples
  • 2.2. Serious imbalances in funding statistical programs
• 3. Privacy and data sharing
  • 3.1. Provincial and territorial data sharing
• 4. Microdata access
  • 4.1 Modernizing the Microdata Access Program
• Definitions
• Endnotes

Executive summary

Statistics Canada's central role as an independent national statistical organization has never been more critical to meeting the need for timely and high-quality statistics in Canada. Having an independent and trusted source of official statistics provides a solid foundation for government accountability and evidence-based decision making by both the public and the private sectors for the benefit of all Canadians.

The fast pace of social and economic change is affecting the kinds of data and analyses Canadians need. There has also been a dramatic shift in how Canadians receive information, with a proliferation of information from new sources, such as social media. New tools are being used to collect, process, transform and visualize information. For Canada to succeed in this dynamic digital economy, Statistics Canada must play a central leadership role, coordinating with governments and organizations to produce coherent and trusted national statistical information.

Canadians have provided personal data to Statistics Canada for over 100 years. The confidentiality of their information is protected under the Statistics Act, and, under federal data protection laws, Statistics Canada must respect the privacy of Canadians. There should be no conflict between respect for the privacy of Canadians and the need for Canadians to provide data to Statistics Canada.

1. Introduction

Statistics Canada's central role as an independent national statistical organization has never been more critical to meeting the need for timely and high-quality statistics in Canada. Having an independent and trusted source of official statistics provides a solid foundation for government accountability and evidence-based decision making by both the public and the private sectors for the benefit of all Canadians. These decisions affect everybody's daily lives, including their health, where they live, where they work and their wages.

Fundamental to public trust is the clear independence of the country's national statistical office, where high-quality statistics and pertinent statistical analyses are produced with objective methods and with outputs that are accessible to everyone. The requirement that statistical information not be subject to political pressure and not serve special interests must be well recognized. This way, even people who may not trust their government can trust the statistical results and, just as importantly, entrust their information to Statistics Canada.

Canadians have provided personal data to Statistics Canada for over 100 years. The confidentiality of their information is protected under the Statistics Act, and, under federal data protection laws, Statistics Canada must also respect the privacy of Canadians. There should be no conflict between respect for the privacy of Canadians and the need for Canadians to provide data to Statistics Canada.

The fast pace of social and economic change is affecting the kinds of data and analyses Canadians need. For example, with the growth of online shopping, Statistics Canada requires new methods to measure consumer spending. Data on consumer spending are used to produce the Consumer Price Index, which Canadians depend on as a measure of inflation that affects wages, pensions, the cost of goods and interest rates. There has also been a dramatic shift in how Canadians receive information, with a proliferation of information from new sources, such as social media. New tools are being used to transform and visualize information, with significant increases in the flows of information, the extent of interconnectedness, and the development of increasingly powerful artificial intelligence software.

Not all available data sources are of good quality, nor do they all take measures to protect the privacy of personal information. Big datasets (usually characterized by their high volumes of data, speed of updates and variety of formats) and web-scraped data (data extracted from websites) are important new sources of data. However, their value for statistical analysis often has significant limitations, such as the underrepresentation of people with certain social or economic characteristics.

For Canada to succeed in this dynamic digital economy, Statistics Canada's role is key. The agency not only has the mandate to produce high-quality national social and economic measures, as well as more disaggregated statistical portraits, it also must play a central leadership role in coordinating data collection and integration with governments and organizations to produce coherent national statistical information for the benefit of all Canadians. This includes supporting leading-edge analysis of this statistical information.

Statistics Canada is responding to these challenges by developing, piloting and deploying new data sources, collection techniques and modelling to add depth and agility to its statistical programs. It has also engaged with Canadians in new ways—for example, using social media to encourage participation in web panel surveys and crowdsourcing surveys. At the same time, the federal government needs to seriously commit to starting a dialogue to address persistent, systemic data gaps. In some key sectors, fragmented data and an unwillingness to share data across jurisdictions have hampered Statistics Canada's ability to create needed nationwide datasets on a timely basis to address the country's most complex and dynamic challenges.

2. National data strategy

Nationwide data are a key strong foundation for decision makers and governments at all levels, as well as the general public, to understand and address important social, health, economic, environmental and energy issues facing Canadians.

Canada does not have a proactive national data strategy that considers the information needs of both today and the future and that puts in place new data sources to inform and anticipate emerging issues and concerns. Throughout its history, Statistics Canada has continually modernized its statistical programs to provide Canadians with the nationwide data and statistical information they need.

Its current modernization initiative is in response to a rapidly evolving digital economy and society. However, there are important data gaps in sectors such as health, energy and the environment, and a lack of sociodemographic detail, including about racialized and Indigenous groups, in social and economic indicators.

New governance mechanisms are required to formally open new dialogues on national data needs and how to best collect and share this information. This must be led by Statistics Canada, in accordance with its mandate, with the full support and funding of the federal government. It must also include all levels of government and statistical organizations. Without a national data strategy, bureaucratic inertia and other hindrances to collecting and sharing statistical information across jurisdictions will continue to outweigh efforts to develop needed nationwide data accessible to all Canadians.

A national data strategy could include First Nations, Inuit and Métis organizations that are planning, implementing and exercising control over the delivery of services to their communities. The nature of the data and analytical skills they require is changing and is more specific to regional and local issues that affect their peoples. Collection for new data needs could be done in partnership with Statistics Canada and other departments. This includes, for example, the need for data to support indicators of well-being, resiliency, understanding, and measurable progress on reconciliation and economic measures.

Statistics Canada is well positioned to lead the various dialogues on national data and information needs. Its proven operational infrastructure provides an essential foundation, given that the agency has developed statistical data from hundreds of federal, provincial and territorial administrative data files. Its expertise in developing high-quality data using standardized concepts and classifications is recognized internationally. Statistics Canada also has the ability, with the required confidentiality protections in place, to combine and link these data with data from other sources to produce the statistical information needed to address national data gaps.

Statistics Canada must build on the new avenues of collaboration created as governments and experts came together in response to the COVID-19 pandemic. This involves working with governments at all levels, other organizations, and new public and private sector partners to produce nationally comparable data that are representative of all Canadians. It also involves developing a close relationship with Canadians to better understand how to maintain their trust as an independent national statistical office and being transparent with regard to the privacy and confidentiality of Canadians' personal information.

Statistical data requirements and funding should be explicitly included in the planning for all federal government programs. There is presently no standard or coordinated way to assess priority data requirements within the federal government. Statistics Canada works closely with most federal departments and organizations in reviewing their data needs. However, these discussions tend to involve only one or two departments at a time, reducing the scope and richness of the information collected. Statistics Canada is also often not actively consulted in the planning of new federal programs, limiting the statistical measures that should be produced.

The federal government should enable Statistics Canada to work collectively with all departments to establish, maintain and act upon a national data strategy that recognizes the interactions between economic, social, health, environmental and energy issues. Data and statistical information should be formally integrated in federal planning processes to more aptly measure, monitor and evaluate federal program outcomes.

2.1 Critical data gaps

It is essential that the country's decision makers have high-quality data and statistical information that represent all regions of Canada and the full range of experiences of individual Canadians. Statistics Canada's current statistical output is vast. Users can access statistical tables, data files and analyses on just about any topic of interest.

At the same time, these data do not always tell the whole story. Information that spans the social, economic and geographic spectrum is often not available. The rapid rise of the digital economy and the impacts of climate change on the environment are examples of areas where new types of data are required to measure impacts on Canadian society and on the Canadian economy. Understanding the barriers faced by racialized groups and Indigenous Peoples also requires more detailed and disaggregated data on employment, income, health and justice.

This year's report focuses on two areas where critical data gaps have long existed. These have become especially evident recently, with the COVID-19 pandemic and increased global awareness of racial inequities.

Data gaps on health and health care

Experts have been saying for years that national health data in Canada are seriously deficient, resulting in inadequate measures of the population's health status and the functioning of the health care sector. Rectifying this situation must be a top national statistics priority. Federally, health data are collected primarily by Statistics Canada (health status and health care) and the Canadian Institute for Health Information (health system performance).

A substantial amount of health data presently exists within provincial and territorial jurisdictions, and it is increasing as hospitals and community clinics adopt new technologies to collect and use health information. This information has tremendous potential for national research on health care and population health. Yet Canada-wide health data are largely fragmented, often unavailable and inconsistent.

This became quickly apparent during the COVID-19 pandemic, when key health data were seriously lacking and inadequate for providing decision makers with the statistical indicators they needed. For example, basic information on COVID-19 confirmed cases and deaths, as well as more detailed information such as that found in hospital records, suffered from delays, incomplete and missing data, and inconsistent definitions across jurisdictions.

These data gaps and inconsistencies have led to serious shortcomings in the timeliness, completeness and quality of Canadian health care and health outcome data. In turn, this has greatly impaired the ability of governments at all levels to monitor and assess the evolution of the pandemic, let alone address serious health issues in Canada.

Barriers to national health data

Provincial, territorial and regional health authorities collect institution-specific health data primarily to administer health care services within their own jurisdictions. Consistency across regions in concepts, definitions, specific data elements collected and completeness of records is often not a priority. It takes months and sometimes longer for information as basic as that from death certificates to become part of the nationwide data that are needed to track deaths related to the pandemic. The methods used to collect medical records from hospitals and community clinics also range widely, from faxed documents to electronic records transferred directly to centralized health care databases. As well, the various software systems designed to collect and retain information such as medical records are often incompatible, limiting the information public health agencies have on important areas.

Some health authorities have invoked provincial data protection laws as barriers to sharing certain information outside their borders. However, the sharing of identifiable data with Statistics Canada is permitted under their data protection laws, in accordance with the Statistics Act. There is also a strong reticence on the part of many provincial and territorial health organizations and communities to share data across health care systems within Canada. Some health officials do not feel that their programs should be subject to scrutiny outside their jurisdiction.

A national health data infrastructure is essential both for supporting health policies and the health care Canadians receive and, more specifically, for managing emergencies such as the current pandemic. The federal government transfers billions of dollars annually to the provinces and territories to help fund health care services, with increases likely in the future for long-term care and possibly pharmacare. The funding of these services must include a provision for nationally comparable health data to measure the state of health and health care in Canada, and the functioning of the health care sector.

Data gaps on racialized groups and Indigenous peoples

The ability to address barriers faced by racialized groups and Indigenous peoples in Canada is seriously hampered by the lack of timely, consistent and disaggregated data.

While the data gaps are not new, recent events in Canada and the United States have brought them to the forefront. For example, the data needed to properly examine the impact of the COVID-19 pandemic on the health and well-being of racialized groups, particularly Black Canadians, and Indigenous communities have not been available. Public outcry has increased following the deaths of Black people at the hands of police officers in the United States and Canada. Supporters of movements such as Black Lives Matter and Indigenous Lives Matter are demanding reforms to address systemic discrimination in areas such as health, employment, housing and justice.

Canada is among the world's most ethnically diverse countries. More than one-fifth of Canadians identify as belonging to a visible minority group. This proportion is projected to increase, as they represent a large majority of new immigrants to Canada, particularly in large cities.

Despite their growing numbers, there have been relatively few national studies of how these groups are faring in Canada. With the census as the main source of information, reports tend to be descriptive profiles of immigrants, visible minorities and Indigenous groups, including general analyses of changes in housing, employment and income. Much of the information available to decision makers is highly aggregated, partial and anecdotal.

Canada needs much more comprehensive data to inform the current debates on the barriers many Canadians face to fully engage in all aspects of society and the economy. It is essential to look beyond the census for high-quality statistical information disaggregated by racialized and Indigenous groups that integrate elements such as family, housing, education, employment, income and well-being.

Surveys generally do not have a large enough sample size to produce detailed disaggregated data, though the Canadian Community Health Survey, the Indigenous Peoples Survey, and more recently, the Labour Force Survey do provide general trends for visible minorities and for Indigenous people living off reserve.

To make inroads in developing a national infrastructure for data by race and by Indigenous group, the focus must include governments' administrative data in areas such as labour, education, health, housing and justice. While a large number of federal, provincial and territorial government departments and organizations already share their administrative data with Statistics Canada, few of these sources include data by racialized and Indigenous groups.

There is pressure from many Canadians and decision makers for government departments to begin incorporating information on race and on Indigenous peoples into their datasets for statistical purposes. Some Canadians may hesitate to share this information with government authorities, but, at the same time, many within these groups have long called for authorities such as police forces to collect this information.

There have been encouraging initiatives. Statistics Canada is presently in discussions with the Public Health Agency of Canada and the Canadian Institute for Health Information on how nationally standardized concepts and definitions must be applied to their planned collection of race-based health data. Also, Statistics Canada and the country's police chiefs have agreed to collect this information when compiling information on victims and accused people to address data gaps for Indigenous peoples and other sociodemographic groups. Statistics Canada has also created the Advisory Committee on Ethnocultural and Immigration Statistics and the Working Group on Black Communities in Canada to counsel the agency.

Statistics Canada is engaging with national Indigenous organizations to provide statistical capacity building that is grounded in the needs of Indigenous peoples. Efforts are being made to identify where data gaps exist and how Statistics Canada data sources and expertise can help improve data quality and access, and support decision making. Statistics Canada's "Statistics on Indigenous peoples" web portal enables users to access data on Indigenous communities on topics such as children and families, health and well-being, education, and work.

Nevertheless, critical data gaps remain, and more needs to be done to address them.

2.2 Serious imbalances in funding statistical programs

It is important that public and private sector decision makers have high-quality data and statistical information that represent all regions of Canada and the full range of circumstances of individual Canadians. Stable core funding for Statistics Canada's programs is essential to having this information. Statistics Canada is given the resources to produce economic indicators for about 20 key areas of economic activity, such as the gross domestic product (GDP), consumer prices and employment. During the COVID-19 pandemic, the agency has been able to continue producing these data, which are critical for assessing the economic impact of the crisis. However, there is an increasing focus on social and environmental data, which measure other important contributors to well-being, beyond the traditional economic measures. This is reflected in a growing international consensus on the need to go beyond the GDP, recognizing that social, health, economic and environmental factors all affect people's well-being. How these various factors interact and affect each other also has significant impacts on individuals, as well as on national and regional economies.

Many of Statistics Canada's key social statistics programs, and certain economic, environmental and energy programs, are largely dependent on ad hoc funding and cost-recovery transfers from federal departments. Support for these programs is often based on the siloed needs of one or two departments. These programs' vulnerability to cuts can significantly affect important and more comprehensive data needs and areas of research. Stable core funding for these programs is essential to support a national data strategy that includes all factors affecting society and the economy.

3. Privacy and data sharing

Statistics Canada has the authority under the Statistics Act to collect personal data to produce the social and economic statistical information that forms the foundation for data-driven decision making for the well-being of all Canadians. For over 100 years, Canadians have provided this information to Statistics Canada, which has maintained the confidentiality of these data and produced statistics without revealing identifiable information about individuals, in accordance with the Statistics Act.

It is essential that citizens understand the importance of evidence-based decision making for Canada to succeed in the new data economy. Governments also need to recognize that traditional ways of collecting information are no longer sufficient. They must support Statistics Canada in its work to provide the key statistical information needed by governments and Canadians to address the increasingly complex and dynamic challenges they face.

There should be a more extensive conversation with Canadians about the alignment between privacy and the need for data for effective decision making. This discussion would facilitate mutual understanding by Canadians and governments of the issues at hand and provide a forum for the exchanges that need to occur for Canada to truly benefit from an independent and trusted source of official statistics. The country needs a solid foundation for government accountability and evidence-based decision making by both the public and the private sectors.

Statistics Canada has been working with expert groups in Canada and with national statistical offices from around the world to explore the possibility of producing high-quality statistics from digital administrative data—both data from governments (e.g., tax files, health care encounters, property tax assessments, driver's licences) and big data from the private sector (e.g., retail transactions, credit card transactions, mortgages, other debt). Being able to use these new, primarily electronic, sources of data will enable Statistics Canada to address the critical needs for new and more disaggregated data in Canada—data that are integrated across the social, health, economic, environmental and energy domains.

Many countries are reviewing their data protection laws, given both the dramatic increase in the prevalence and use of personal information from administrative data, and growing concerns about the data holdings of multinational social media companies. In doing so, they recognize the importance of collecting personal information for specific legitimate purposes, when done under the country's legal authority and in a transparent manner. For example, the European Union's General Data Protection Regulation recognizes the need for national statistical offices to access personal information, permitting the flow of the information for statistical research for the public good, without requiring consent.

In Canada, Statistics Canada's project to collect detailed data on banking and credit card transactions has drawn particular attention. These new sources of information are key to addressing emerging critical data gaps in Canada's economic and financial measures as a result of important changes to consumer patterns and debt. In response to concerns raised by some Canadians, Statistics Canada suspended its work to address them before proceeding with the project. The agency is also collaborating with the Office of the Privacy Commissioner to address concerns as a result of complaints it received about this project. After investigating these complaints, the Privacy Commissioner of Canada concluded that Statistics Canada was not in contravention of the Privacy Act.

The need for transparency on matters of privacy and confidentiality is essential to maintaining public trust. Statistics Canada must clearly inform Canadians why the information it collects is needed and explain the measures it takes to protect the confidentiality of Canadians' personal information. The need for transparency is especially heightened in this project, given the sensitivity of personal banking information and the volume and detail of information that may be collected.

Moving forward, the agency needs to engage with a focus on guiding principles to meet the rapidly changing data context. Statistics Canada is working in consultation with the Privacy Commissioner of Canada to develop a new methodology framework based on the principles of necessity and proportionality. This methodology framework, which the agency is sharing with the global statistical community, is a significant and thoughtful initiative.

The framework recognizes Statistics Canada's legal authority under the Statistics Act to collect personal information for statistical purposes, and Statistics Canada's legal obligation under the same act to ensure the confidentiality of this information. The framework also recognizes the country's data protection laws. These include the federal Privacy Act, which sets out how personal information held by the federal government and federal public sector institutions is used, stored and shared, and the Personal Information Protection and Electronic Documents Act, which sets out how organizations engaged in commercial activities must handle personal information.

3.1 Provincial and territorial data sharing

The provinces and territories have a long history of sharing administrative data with Statistics Canada in areas such as vital statistics, education and justice. Statistics Canada has the authority to collect these data under the Statistics Act, and most provinces and territories have provisions in their data protection laws to enable them to share data for statistical purposes for the public good.

For many years, some provincial and territorial health authorities have invoked provincial data protection laws as barriers to sharing certain health data. This has contributed in part to the poor state of national health data, as seen during the COVID-19 pandemic. In response to questions about privacy issues during the pandemic, the Privacy Commissioner of Canada stated that, "During a public health crisis, privacy laws still apply, but they are not a barrier to appropriate information sharing."

Discussions about data sharing must be broadened to include priority needs for national data. To make measurable progress, Statistics Canada must have federal government support to play a leadership role and build on the new avenues of government collaboration created in response to the pandemic.

Many provinces and territories are reviewing their data protection laws to take into account new technologies for collecting and sharing personal information. Statistics Canada must work with them to ensure that revisions to data protection laws recognize the importance of official national statistics and that there are no legislative ambiguities with regard to Statistics Canada's legal authority to collect data from their jurisdictions.

4. Microdata access

The need for a modern infrastructure to access Statistics Canada's microdata, including secure remote access, has never been greater, as duly authorized researchers look to inform governments and Canadians on issues such as the social and economic impacts of the COVID-19 pandemic.

To meet the specific information needs of Canadians, the agency has introduced web portals to transform complex data into easy-to-understand visuals. The "COVID-19: A data perspective" portal is a good example. Created in response to the pandemic, it provides governments and Canadians access in one place to a wide array of relevant health, social and economic statistical information with tables, infographics, interactive maps, data visualizations and statistical analyses.

For many years, Statistics Canada has provided students and researchers with a range of ways to access data, with strict security restrictions for access to confidential microdata. Non-confidential Public Use Microdata Files are used extensively by postsecondary students through the Data Liberation Initiative. Students and duly authorized researchers can also use the online Real Time Remote Access system available for most social surveys. The output is largely descriptive and useful for general findings and preliminary research activities. It presently requires knowledge of SAS programming, which limits access to the data for some researchers.

Confidential microdata can be accessed through Statistics Canada's Research Data Centres (RDCs). These are secure facilities located on university campuses that offer access to Statistics Canada's more detailed—and therefore most analytically powerful—data holdings. They include detailed microdata from Statistics Canada's household surveys, census data and an increasing number of administrative datasets such as the cancer registry. Since the opening of the first RDC in 2000, the Canadian Research Data Centre Network has expanded and now includes over 30 secure data laboratories in which over 2,000 duly authorized researchers across Canada conduct advanced quantitative social science and health research.

Secure access to anonymized business and economic microdata is provided to government researchers through the Canadian Centre for Data Development and Economic Research Program at Statistics Canada headquarters in Ottawa.

4.1 Modernizing the Microdata Access Program

The RDCs, with their physical data laboratories, have become outdated and are no longer able to adequately support Canada's research and analysis needs. The COVID-19 pandemic has made clear the need for Statistics Canada to transition from the RDCs' physical infrastructure to new distributed modes of access. Once a world leader, Statistics Canada has fallen behind. The agency is currently modernizing its microdata access infrastructure with more sophisticated datasets, secure remote access technologies and expansion of secure access to anonymized business data in the RDCs. This is a long-awaited initiative that will greatly improve the quality and depth of research and analysis in Canada across all sectors. However, the timeline of well into 2022 for full implementation of secure remote microdata access is too long and should be accelerated.

With the wealth of statistical information, data expertise and technical savvy found in public, academic and private institutions across the country, there are tremendous opportunities to transform how data are developed and used in Canada. Researchers in Canada currently have secure access to a vast amount of data from a wide range of sources, including from government administrative data sources, universities and the private sector. The explosion of big data and data analytics is also generating a growing pool of talented data scientists. A modernized research data access program will greatly facilitate and support the statistical research required to address the increasingly complex and multifaceted issues faced by Canadians.

Statistics Canada must also modernize and streamline its administrative processes, such as the authentication of researchers. Statistics Canada should look to international models such as that used in the Netherlands, where the authentication process includes a class of "duly authorized researchers" who may be required to take training on privacy and security and must be affiliated with a government department, university or institute for scientific research. As in Canada, research must be for statistical purposes as opposed to private commercial research.

There is also interest from national and regional Indigenous organizations in developing and implementing information and research data centres in their communities. This would provide Indigenous peoples with better access to Statistics Canada microdata and other Indigenous microdata on the health, social and economic well-being of Indigenous communities. Analytic capacity would also be expanded to include the use of new data, analytic techniques and technology to support research, planning and development and to build statistical capacity to assist vulnerable Indigenous communities.

Endnotes

1. "Factors associated with COVID-19-related death using OpenSAFELY," Nature, July 2020.
2. The Employment Equity Act defines members of visible minorities as "persons, other than Aboriginal peoples, who are non-Caucasian in race or non-white in colour." Many data users use visible minority as a proxy for race.
3. "Commissioner publishes framework to assessprivacy-impactful initiatives inresponse to COVID-19."
4. Statistics Netherlands, "Microdata: Conducting your own research."

Under the authority of the Statistics Act, Statistics Canada is hereby requesting the following information, which will be used solely for statistical and research purposes and will be protected in accordance with the provisions of the Statistics Act and any other applicable law. This is a mandatory request for data.

• Employment and remuneration
  • Gender of federally appointed judges
  • List of employees and work email addresses for Government employees working in Nunavut
• Revenue and expenditures
  • Data on support for businesses through the Business Innovation and Growth Support (BIGS) programs

Employment and remuneration

Gender of federally appointed judges

What information is being requested?

Statistics Canada is requesting a list of federally appointed judges, including the following variables: first and last name (or a unique identifier), gender (or sex), type of court, location (of court), and appointment start date and appointment end date (or removal).

What personal information is included in this request?

This request contains personal information such as the first and last name (or unique personal identifier) and gender (or sex) of federally appointed judges. The personal identifiers are required to perform data processing activities only, such as removing duplicates from files, imputing missing values (if necessary) and tracking records over time. Only aggregate statistics will be disseminated.

What years of data will be requested?

Annual data as of 2018 is being requested.

From whom will the information be requested?

This information is being requested from the Office of the Commissioner for Federal Judicial Affairs Canada

Why is this information being requested?

Introduced in Budget 2018, the Gender Results Framework (GRF) represents the Government of Canada's vision for gender equality. The GRF contains 43 indicators designed to track how Canada is currently performing; define what is needed to achieve greater equality and determine how progress will be measured going forward.

Greater gender balance and diversity in the judicial system will enable the system to be more responsive to the differing needs and situations of all Canadians.

Statistics Canada is requesting this information to create and publish statistics on the gender distribution of federally appointed judges. These statistics will be used by policy makers and researchers to track the gender distribution of federally appointed judges over time.

Statistics Canada may also use the information for other statistical and research purposes.

Why were these organizations selected as data providers?

The Office of the Commissioner for Federal Judicial Affairs Canada (FJA) is responsible for collecting demographic information on judicial applicants and appointees based on voluntary disclosure by candidates through self-identification.

When will this information be requested?

December 2020 and onward (yearly)

What Statistics Canada programs will primarily use these data?

Gender Statistics Program

When was this request published?

December 3, 2020

List of employees and work email addresses for Government employees working in Nunavut

What information is being requested?

Statistics Canada is requesting employee information for government employees working in Nunavut to create the Nunavut Government Employee Survey (NGES) survey frame. The requested information includes employee lists containing their Personal Record Identifier (PRI), full name, sex, date of birth, department name, and work email addresses.

What personal information is included in this request?

This request contains personal information such as the employee's PRI, first name, last name, sex, date of birth, work email address, and department name.

Personal identifiers, including PRI, first name, last name, sex, date of birth and department name, are necessary to update the survey frame and facilitate data linkages for statistical purposes only. The data will be linked to federal employee payroll files, which are currently used by Statistics Canada, to create the NGES survey frame. Once the data are linked, all direct identifiers - such as names, addresses, telephone numbers, or any other identifying information - will be removed and the data will be anonymized.

What years of data will be requested?

The NGES is conducted every five years.

Data will be collected starting with the 2021 reference year.

From whom will the information be requested?

This information will be requested from government departments with employees located in Nunavut.

Why is this information being requested?

Article 23 of the Nunavut Agreement aims to increase Inuit participation in government employment to a representative level through an ongoing Nunavut Inuit Labour Force Analysis (NILFA). By strengthening Inuit representation in public institutions in Nunavut, the NILFA is supporting Inuit self-determination. As a signatory to the Nunavut Agreement, the NILFA is a federal government obligation.

Statistics Canada is requesting this data to verify and update employee payroll data (already held by Statistics Canada's Centre for Labour Market Information Division) which is used to create the Government of Canada component of the NGES frame. Work email address will also be used to send the electronic questionnaire link to Government employees in Nunavut.

As part of the NILFA, the NGES was designed to collect data on Inuit enrolled under the Nunavut Agreement regarding their availability, interest and level of preparedness for government employment. This data informs the development of Inuit Employment Plans and Pre-Employment Training Programs within both the Government of Nunavut, as well as the Government of Canada within Nunavut.

Nunavut Tunngavik Incorporated, which represents the interests of Inuit enrolled under the Nunavut Agreement, and a member of the NILFA Technical Working Group, supports this data acquisition. Without the acquisition of these data, Statistics Canada would not be able to ensure all individuals in the NGES target population are identified on the survey frame. Furthermore, the agency would not be able to send out the electronic questionnaire link to the survey sample of Government employees in Nunavut, ultimately excluding them from the survey.

Statistics Canada may also use the information for other statistical and research purposes.

Why were these organizations selected as data providers?

These organizations meet the definitions in Article 23 of the Nunavut Agreement because they are Federal departments that have offices in Nunavut, and Treasury Board is their employer.

When will this information be requested?

Starting in September 2020

What Statistics Canada programs will primarily use these data?

The Nunavut Government Employee Survey (NGES)

When was this request published?

February 10, 2025 

Summary of Changes

Language has been updated to make it clear that this is an ongoing request as the NGES occurs every five years.

Revenue and expenditures

Data on support for businesses through the Business Innovation and Growth Support (BIGS) programs

What information is being requested?

Information on the support granted through the governmental BIGS programs. Such information includes the value of support, the transaction dates, the types of support, the names of the beneficiary enterprises, their business number, their contact information, the project numbers, the effective dates of the agreements, and the amounts of the agreements.

What personal information is included in this request?

This request does not contain any personal information.

What years of data will be requested?

Open-ended, data beginning with the 2007 reference year.

From whom will the information be requested?

From all federal departments or agencies that have Business Innovation and Growth Support (BIGS) programs.

Why is this information being requested?

Statistics Canada requires this information to produce and publish statistics on government programs that support business growth and innovation. These statistics will help Statistics Canada, together with the Treasury Board Secretariat, identify the impacts of business innovation and growth support programs. The data will also be used by policy makers, researchers and stakeholders to assess and measure the performance of these programs.

Statistics Canada may also use the information for other statistical and research purposes.

Why were these organizations selected as data providers?

These organizations collect information on the business innovation and growth programs they administer and keep that information up to date.

When will this information be requested?

Starting in April 2021

What Statistics Canada programs will primarily use these data?

Business Innovation and Growth Support (BIGS)

When was this request published?

March 26, 2021

Statistical information

Description

Statistics Canada produces objective, high-quality statistical information for the whole of Canada. The statistical information produced relates to the commercial, industrial, financial, social, economic, environmental and general activities and conditions of the people of Canada.

Results

Statistics Canada has always fostered a culture of innovation. Change is constant, and the agency's modernization journey will continue to change the way it does business to meet the needs of Canadians.

The modernization journey revolves around five key pillars, which were developed in collaboration with stakeholders and data users to better understand their information needs.

• Ensure staff are empowered in a modern and flexible workplace
• Provide user-centric service delivery to focus resources on what clients want and need today
• Collaborate and engage with partners, share expertise, and increase access to data
• Help build statistical capacity with partners and foster data literacy among Canadians so they can effectively use the agency's data
• Use leading-edge methods.

The agency helped Canadians understand the story behind the data through many statistical capacity, data literacy and communications initiatives. Assisted by new methods and numerous collaborative partnerships, the agency expanded its data holdings and access to data. At the same time, the agency properly managed risks, prepared for the 2021 Census and delivered on key priorities, such as providing more disaggregated data on topics such as gender, region and ethnicity.

In 2019–20, Statistics Canada was able to adapt quickly to the new reality caused by the COVID-19 pandemic thanks to the advances it had already made toward a modern and flexible workplace.

Modern and flexible workplace

As part of its modernization initiative, Statistics Canada changed the way it works, manages its teams and meets organizational goals, including risk mitigation. This transformation brought about a cultural shift, in line with Blueprint 2020, by focusing on building a modern, capable and high-performing workforce.

A corporate culture change was initiated to make Statistics Canada a more agile, flexible and responsive organization. The agency's vision of a modern and flexible workplace is a workplace that fosters a culture of innovation and connectivity, and that improves how it and its mobile employees leverage digital technology and space.

The agency introduced four new culture values: curious and always learning, purposeful, trustworthy, and caring and inclusive. These values were designed to help guide employees throughout the modernization journey. A wide range of activities took place during 2019–20 to help promote these values, including a learning fair, panel discussions and the development of a Culture Passport.

The agency's ability to react to the COVID-19 pandemic demonstrated the progress made in this cultural change. Statistics Canada established a COVID-19 Task Force on January 27, 2020, before the pandemic hit North America, to monitor the latest information globally and within Canada. When the Ontario government announced that citizens must take exceptional public health measures to protect themselves from the virus, the agency transitioned to an entirely remote workforce on March 13, 2020. This included successfully transitioning approximately 7,500 employees to remote working overnight, and invoking only 12% of the agency's business continuity plans. All 22 mission-critical operations were kept fully operational within the existing bandwidth and remote access capabilities. Communications to all staff and senior management continued daily throughout March 2020 to keep employees informed of changing business operations and health and safety measures.

Statistics Canada has also activated new programs that provide critical specialized data and statistics that are needed to accurately model and track important topics, such as personal protective equipment, contact tracing, and targeted economic and social statistics. These new programs inform decision makers on the current situation in Canada and how to adjust their policies to best suit the needs of Canadians on a daily basis.

Mitigating risk in an agile manner

To meet Canadians' current and emerging data needs in a timely, responsive and agile manner, Statistics Canada continuously monitors its internal and external environment to develop risk mitigation strategies. The agency has a flexible integrated risk management framework to systematically identify, understand, manage, monitor and communicate risk. With the new corporate culture in mind, the agency identified several key potential risks for 2019–20:

• the loss of relevance and responsiveness
• the impact of modernization and transformation initiatives
• the loss of public trust
• statistical errors; and
• breaches in confidentiality

To address these risks, the agency continued to adapt and to evolve its governance oversight by implementing a principled performance model and by creating a Governance, Risk and Compliance (GRC) Division that will offer a well-coordinated and integrated approach to reliably achieve objectives while addressing uncertainty and acting with integrity. More specifically, during 2019–20, the GRC Division implemented key principles for risk-based governance to increase the effectiveness of the internal governance structure. This included ensuring that governance is informed by risk, and assigning clear accountabilities to each committee to drive strategy to reach identified strategic outcomes. Namely, the agency

• refreshed and streamlined the internal governance structure for tier-level committees
• clarified the terms of reference for all existing and newly formed committees to ensure strategic, risk-based governance with focused work plans
• developed standardized processes and tools to effectively and efficiently manage governance committee meetings and track performance.

To complement internal governance systems, the agency also relied on the advice and recommendations of external governance bodies, such as the Departmental Audit Committee (DAC) and the Canadian Statistics Advisory Council (CSAC). The DAC provides assurances on the adequacy and effectiveness of Statistics Canada's management systems, and the CSAC provides information to the Chief Statistician and the Minister on the overall health of the national statistical system.

With their inaugural meeting in July 2019, the Advisory Council on Ethics and Modernization of Microdata Access (ACEMMA) provided guidance to Statistics Canada on data access, privacy and data governance to maintain and support the data needs of Canadians. The ACEMMA has a wealth of knowledge and experience in ethics and will help support the agency's overall risk mitigation strategy when considering new data sources.

The agency sought to further strengthen the trust of Canadians by showing how it protects their privacy every day. In 2019–20, through the Trust Centre, and social media platforms, the agency released an infographic called Administrative data: Why it matters to you, and five infobytes based on Joe Anonymous, a video that makes these important concepts accessible to all Canadians in a visual format. The Trust Centre, is managed in a responsive manner, with new material added regularly.

As a further step, the agency made investments—both technological and methodological—to ensure the reliability, timeliness, scalability and security of its data.

• The agency developed a Confidentiality Classification Tool, which classifies confidential data against a set standard along a continuum of disclosure and sensitivity risk.
• The Statistics Canada Quality Guidelines were updated and published. This document brings together improved guidelines and checklists for issues to be considered in the pursuit of high-quality statistics.
• Errors in The Daily were minimal because of improved internal procedures, including increased automation and more rigorous monitoring.
• Security training continued to be a priority for new and existing employees, and was reinforced and validated with regular physical security sweeps. The use of more engaging and user-friendly communications continued.

User-centric service delivery

Statistics Canada's focus on user-centric service delivery is about ensuring that users have the information they want when they want it and how they want it. Through engagement and outreach activities, Statistics Canada learned that Canadians wanted more visuals, which make the data easier to understand. However, many partners with higher data-literacy skills still wanted data tables.

To meet Canadians' diverse range of needs, the agency provided information on its website in various formats, including data tables, infographics, interactive maps and other data visualizations.

In 2019–20, Canadians could access 37,254 data products on the Statistics Canada website and 7,368 data tables through the open government portal. In 2019–20, there were just under 20.3 million visits to the agency's website—making it one of the most visited federal government websites. For users who preferred to obtain data through application program interfaces (APIs), the agency received over an average of 250,000 API calls per month.

The agency has created a number of portals to improve user experience. These portals are gateways or hubs for accessing all Statistics Canada's information on a particular subject. In 2019–20, 21 new portals were created. In 2018–19, there were just two. These new portals provide improved access to data on the motor vehicle sector, seniors and aging, Indigenous peoples, poverty, health, housing, price indexes, education, courts, correctional services, economic accounts, agriculture and food, business and consumer services, travel and tourism, and culture statistics.

Data visualizations, including online interactive tools and static infographics, provide data to Canadians in an easy-to-use and visually appealing format. In 2019–20 alone, the agency added 89 infographics, bringing the agency total to 251 infographics.

Similarly, to meet the needs of Canadians, the number of interactive data visualization tools continued to climb. Out of the agency's total of 82 data visualization tools, 39 were created in 2019–20. This fiscal year, visualization tools were created for a broad range of themes, including transportation, immigration, income, crime, education, imports and exports, price indexes, retail commodities, Internet use, gross domestic product, trade, and housing statistics.

Videos were used more often and more strategically, with 30 weekly videos released on gross domestic product, the Consumer Price Index and the Labour Force Survey. More than 30 other videos were created for tailored subjects, such as data in a changing world, modernizing to serve Canadians, the 50th anniversary of the Official Languages Act, and the faces of Statistics Canada.

Statistics Canada also provided Canadians with data insights through 1,229 articles in The Daily, the agency's official release bulletin and the first line of communication with the media and the public. The agency also published 48 issues of The Weekly Review, a summary of the week's top statistical stories, released on the last working day of each week. This product further increases the accessibility of data released through The Daily.

Many Canadians look to obtain statistics through the news media. The media relations team responded to over 2,200 media inquiries and recorded more than 56,000 mentions of Statistics Canada in the national media.

To improve user experience, the My StatCan feature allows subscribers to customize their view of the agency's website, select specific publications and data products, and receive customizable data through email. Over 59,000 data users subscribed to My StatCan in 2019–20, a 7.2% increase in subscribers and 5.3% above the target for the year.

In 2019–20, Statistics Canada improved its ability to share its work through an increased digital presence and increased outreach. The agency now has a presence on Reddit and Instagram, in addition to Twitter, Facebook, LinkedIn and YouTube. Similarly, the agency shared over 2,500 social media publications in 2019–20, and its posts reached over 12.2 million online users. These users engaged with the agency's social media posts over 350,000 times.

In 2019–20 Statistics Canada translated over 6 million words—this ensured Canadians could access to all the agency's information in the official language of their choice. In addition, the agency promoted the use of both official languages through regular messages and activities, including the celebration of the 50th anniversary of the Official Languages Act.

The 2021 Census: New content to count everyone

The census is the largest program at Statistics Canada and has focused on a user-centric delivery model for many cycles. During 2019–20, preparations for the 2021 Census included numerous consultations and partnership activities to ensure that users have the data they need.

Building on the previous year's work of consultations and qualitative testing, in 2019–20, the census questionnaires were tested quantitatively during the 2019 Census Test. The 2019 Census Test evaluated changes to the wording and flow of some questions, as well as the potential addition of new questions. The test also incorporated the evaluation of new communications material and variations to further improve collection methods. The content was tested by a sample of nearly 135,000 households and was reviewed by nine analysis panels.

Agency officials also met with representatives of 14 federal departments and other interested organizations. To better understand the needs of Indigenous organizations and communities, more than 60 in-person discussions were held in 30 Indigenous and non-Indigenous communities across Canada, with more than 400 contributors. Statistics Canada also met with individuals from organizations representing official language minority communities, organizations representing or providing services to Canadians with disabilities, immigrant and ethnic communities and organizations, LGBTQ2 communities, academia, businesses, and non-profit organizations.

Based on the findings from consultations and discussions, Statistics Canada proposed changes to census content to respond to key priorities identified by participants. This included new questions on sex at birth, gender, veterans, minority language rights-holders, Indigenous identity, multiple modes of transportation, and labour market activities. These questions were added so that everyone can see themselves in the census—a key desire heard from Canadians. The 2021 Census will also include new labour and commuting questions. Understanding the changing nature of the labour market and the skills people bring to it is critical for Canada to remain competitive in a global market economy.

“For many decades, we have worked very closely with Statistics Canada. Our countries are very similar in our census: vast geographies and our need to work closely with First Nations people in our work. The StatCan collection innovations that we have mirrored have brought us better outcomes for our populations who have benefitted from greater choice in the ways we interact.”

This rigorous testing in 2019–20 set the stage for a 2021 Census that will provide accurate data needed to support Canadian communities as they evolve, adapt and continue to recover from the COVID-19 pandemic. Already, data from the 2016 Census have been key to the emergency response. In the early days of the pandemic, crucial demographic information on vulnerable populations was provided to public health authorities and emergency services officials. This information was instrumental in informing policy making in the context of the pandemic, and helped guide decisions on where government support was most needed.

Census data users are asking for more information, delivered at an increasingly granular level. Given the work completed in 2019–20, Statistics Canada is prepared to meet these needs while continuing to listen to and engage broadly with organizations and individuals representing various government departments, Indigenous leadership, the general public, communities, the private sector and academics to ensure that the agency remains in touch with the interests and needs of Canadians.

As Statistics Canada progressed with its preparations for the 2021 Census, the agency supported the positive outcomes of the live 2019 Census Behaviour Test to improve statistical and operational processes and the risk posture for the 2021 Census. This was a critical step in ensuring that the 2021 Census collects and disseminates relevant data of the highest quality to support evidence-based decision-making by public and non-public sector users within Canadian society. Statistics Canada worked in close collaboration with Shared Services Canada to take steps to ensure key infrastructure is in place to deliver the 2021 Census.

Collaboration and engagement with partners

A key pillar of the agency's modernization framework is collaboration and engagement with partners, including the sharing of expertise and expanded access to data. During 2019–20, Statistics Canada continued to increase collaboration and engagement.

In the summer of 2019, the agency expanded its focus on collaboration and engagement with partners through organizational changes that included creating a corporate Strategic Engagement Field, led by a new assistant chief statistician and guided by a new innovative strategy.

To foster increased collaboration with other external organizations, many speeches and special outreach and engagement events occurred. Specific external audiences included international statistical officials visiting the agency, and organizations such as the Empire Club, the Canadian Chamber of Commerce and affiliate members, the Federation of Canadian Municipalities, the Canadian Research Data Centre Network, and the Canadian Association of Chiefs of Police.

Statistics Canada took a leadership role on the international stage. Its collaboration with various partners resulted in significant successes and milestones over the past fiscal year. For example, for the Conference of European Statisticians (CES), Statistics Canada led an in-depth review on measuring well-being in digital society, which covered data collection practices in 40 countries. The Chief Statistician and other executives assumed the role of chairperson for multiple international groups. In 2019–20, Statistics Canada assumed the roles of chair, co-chair or member for 14 out of the 18 United Nations Economic Commission for Europe CES working groups.

Creating and sharing data through new partnerships and collaboration

Statistics Canada increased the number of collaborative projects and the sharing of new information during 2019–20. These projects ranged in size, length and formality. During 2019–20, Statistics Canada entered into 1,700 formal agreements with cost-recovery clients and partners to provide custom requests, workshops, statistical surveys and related services.

The agency has greatly increased collaborative activities related to housing statistics. In 2019, in partnership with the Canada Mortgage and Housing Corporation, Statistics Canada shared the results of the new Canadian Housing Survey to provide data on various topics, including social and affordable housing, wait-list times for housing, perceptions of well-being, and social inclusion.

In support of the National Housing Strategy, Statistics Canada also provided data on at-risk veterans. In partnership with Veterans Affairs Canada, the agency used 2016 Census records linked with a cohort of Canadian veterans to produce data on housing affordability, sustainability and accessibility.

Results from these two projects provide information on whether Canadians have housing that meets their needs and that they can afford. This helps policy makers to ensure that more Canadians have access to an affordable home.

In addition to housing statistics, the agency engaged with many partners to gather energy information. In June 2019, Statistics Canada launched the Canadian Energy Information Portal, a first step in creating a hub for energy information to address long-standing concerns regarding dispersed datasets and gaps in energy data that impact researchers, analysts, decision makers, etc. Feedback from portal users and user consultation and focus group testing informed the design of the Canadian Centre for Energy Information (CCEI), with the purpose of providing a convenient hub for information on Canada's energy future. In parallel with this design, the CCEI engaged with a broad base of stakeholders on their data needs and priorities, including participants of the Energy Modelling Initiative, federal partners from Natural Resources Canada, Environment and Climate Change Canada, the Canada Energy Regulator, provincial and territorial energy departments, and industry. The CCEI also established itself on social media with the hashtag #energynews. Foundational work done to document concepts and variables related to energy will form the base of a data standard with which to connect dispersed information.

Statistics Canada participated in other collaborative projects that resulted in increased access to data for partners and allowed them to better meet their organizational goals and public policy objectives that benefit society. The agency

• provided a presentation on key data points to the Standing Senate Committee on Legal and Constitutional Affairs when it was considering the firearms legislation Bill C-71, and to the Canadian Firearms Advisory Committee (responsible for advising the Minister of Public Safety)
• reorganized data from the adult component of the Integrated Criminal Court Survey so that partner organizations could analyze open cases and completed cases, and to create a new series of indicators that will help partners improve the efficiency of Canadian criminal courts
• participated on the Health Canada Task Force on Virtual Care to explore the state of Canada's health data landscape as it relates to virtual care and artificial intelligence
• renewed engagements and outreach with Indigenous leaders, organizations and communities; on multiple occasions, the agency met with President Natan Obed of the Inuit Tapiriit Kanatami and representatives of the First Nations Information Governance Centre to discuss Indigenous affairs
• developed a national and provincial index of marginalization and deprivation, which is based on housing instability, economic deprivation, social and cultural isolation, and reliance on others, and allows for an understanding of inequalities in society
• launched the virtual Federal Research Data Centre at the Canada Mortgage and Housing Corporation to designate a room to allow 24/7 access to 25 researchers
• released 248 new comprehensive datasets for access in the research data centres, representing one-third of the total data available.

Statistics Canada also expanded collaborative activities with partners to help better understand the economic conditions within Canada. The agency

• created new, more granular tourism data that are available more frequently and include comparable measures of expenditures, gross domestic product and employment; for example, the National Travel Survey was expanded from 6 to 13 airports and, in collaboration with Destination Canada, payment data were integrated with survey data to improve visitor spending estimates at the sub-provincial level
• partnered with each territory to produce harmonized, pan-territorial data on both domestic and international travellers to create quarterly tourism indicators for the North
• expanded national and provincial Monthly Survey of Manufacturing data to include 12 census metropolitan areas.

Statistics Canada also participated in unique collaborative efforts with global implications related to the environment. For instance, in collaboration with Employment and Social Development Canada, the agency conducted extensive consultations with other federal departments and organizations to identify Canadian indicators for the Sustainable Development Goals.

Through the agency's leadership role in the development of, and commitment to, global indicators supporting the 2030 Agenda, Statistics Canada published additional indicators, more granular data and new visualizations on the Sustainable Development Goals Hub. The agency also worked with other departments, organizations and subject-matter experts to identify the best data sources for the 60 indicators in the Canadian Indicator Framework and to develop disaggregated data for vulnerable populations.

Using leading-edge methods

As part of the agency's mission to continue to provide trusted insight to Canadians, Statistics Canada strives to find ways to increase access to new and untapped data. The agency is also increasing its use of administrative data, modelling and new leading-edge methodologies to increase data capacity and reduce the response burden on Canadians. This includes the development of the agency's Necessity and Proportionality Framework, which aims to balance society's data needs with the protection of Canadians' privacy.

An increased focus on innovation with data science

Data science enables the integration and efficient use of big and unstructured data sources to create new, high-quality, relevant and easily accessible products. New approaches that integrate data (e.g., from text, satellites, large digital data sources and big data) have been used by Statistics Canada to address evolving expectations in a constantly adapting manner.

For example, electronic scanner databases with sales and product information are now available from major retailers. Statistics Canada uses machine learning to classify all the product descriptions in the scanner data, and then obtains aggregate sales data for each area. This approach has resulted in a high degree of automation and accurate, detailed retail data. It also reduces the response burden for major retailers. The data and machine learning models for the first retailer are now being used in the Retail Commodity Survey and the Monthly Retail Trade Survey, with the other retailers to follow. This approach will also be used for other surveys.

Addressing the opioid crisis in Canada

During 2019–20, in response to a clear data need and with the help of collaborative activities and partnerships, Statistics Canada developed innovative research efforts on opioids.

In June 2019, the City of Surrey Opioid Summit: From Data to Action hosted 60 experts, and Statistics Canada data insights fuelled the discussion. The opioids work undertaken by Statistics Canada highlights the agency's ongoing commitment in support of all levels of government to address the most significant challenges currently facing Canadian communities. Statistics Canada securely and privately gathered data from across various social domains to provide an unprecedented lens for delivering meaningful insights to Canadians on the opioid crisis to inform responses by program and policy makers. Health Canada also provided Statistics Canada with additional funding to expand the Surrey project to the whole of British Columbia, and selected jurisdictions in Alberta and Ontario.

The agency launched a project with Ryerson University to determine the possibility of using machine learning to identify specific causes of death (e.g., opioid-related deaths, cycling-related deaths) recorded in the Canadian Coroner and Medical Examiner Database (CCMED). The CCMED is a unique source of information on preventable deaths, including opioid and other drug overdoses. In addition to the demographic information on the decedent, the CCMED contains information on the circumstances surrounding the death, and detailed narratives on each death investigated by coroners and medical examiners. These narratives provide a rich source of contextual information on the circumstances of a death.

The agency also analyzed the impact of the opioid crisis on life expectancy rates in Canada. Canada has experienced and continues to experience a serious opioid overdose crisis. The impact of the crisis on the Canadian population can be measured in different ways. Life expectancy is one of the most general measures of overall population health, reflecting the number of years a person would be expected to live based on the rates of death in a population in a given year. From 2016 to 2017, for the first time in over four decades, life expectancy at birth did not increase for either males or females. This trend was largely attributable to the opioid crisis.

The innovative linkages combining information on opioid use and socioeconomic data were used to create analytical products, including a profile of opioid users and trajectory analysis to identify events leading to an opioid event. A feasibility study was conducted to identify data sources available to study the impacts of other harmful drugs (e.g., methamphetamine).

Measuring Canada's digital economy

Globally, there is limited intelligence surrounding the value of the digital economy and data. However, its economic importance cannot be denied. To address this data gap, in May 2019, Statistics Canada released "Measuring digital economic activities in Canada: Initial estimates," a digital economic account with estimates of the value of digital economic activities in Canada from 2010 to 2017. These activities included digitalization enablers, such as IT infrastructure, e-commerce transactions and digital delivery to consumers.

In June 2019, Statistics Canada released a new experimental framework to measure the value of data, databases and data science in Canada. Experimental estimates based on this framework were released a month later. Statistics Canada is working with international counterparts to set global standards to measure data's economic impact.

The agency also conducted research to better understand how and where the digital economy fits into the Canadian System of Macroeconomic Accounts and how it can be measured. For example, research is underway on how the widening productivity gap between the most productive firms and all other firms affects the distribution of individual employment earnings.

Measuring government-wide modernization efforts

As announced in Budget 2018, the Treasury Board of Canada Secretariat and Statistics Canada are working together to improve performance and impact assessments for innovation-related programs.

Statistics Canada is using a data-driven approach to create consistent and comparable performance and impact measures for government innovation programs. For example, to measure business innovation, the Entrepreneurship and Linkable File Environment (ELFE) section used administrative data from 18 federal departments to produce a research database to help various government departments evaluate the effectiveness of their programs. The ELFE section also has a visual tool to help analysts track business indicators using a range of variables.

New and improved modernization projects

The agency's modernization culture has inspired innovative projects across the agency. In 2019–20, Statistics Canada developed many new leading-edge approaches to reduce survey response burden on Canadians and provide new, improved or timelier data and services to Canadians.

Among the successes regarding economic statistics, the agency

• gathered data on cannabis consumption using wastewater sampling
• monitored shifts in the clean technology sector and the low-carbon economy
• measured the impact of foreign ownership on housing
• continued to assemble alternate sources of agriculture data, with an aim to reduce the burden on farmers
• used scanner data, web scraping and APIs to supplement the Consumer Price Index
• created interim "flash estimates" for monthly gross domestic product, and other key economic indicators to provide government and private sector analysts with more timely economic signals.

Among the accomplishments achieved in social statistics, the agency

• completed a microsimulation pilot project related to the Saskatchewan criminal justice system that included projections on the potential impact of reducing the education gap between Indigenous and non-Indigenous people
• made arrangements to use administrative correctional services data to replace the enumeration of usual residents in correctional facilities for the 2021 Census
• invested in and supported the development of the new Social Data Integration Platform, which provides a more focused and timely way of producing social statistics, including web panels and crowdsourcing.

Advances were also made in statistical methodologies. For instance, the agency tested privacy-preserving techniques, including homomorphic encryption, which provides data protection for highly sensitive data while enabling data processing. The agency also addressed a broad range of privacy concerns through the development of the Necessity and Proportionality Framework.

Necessity and Proportionality Framework

In December 2019, the Privacy Commissioner of Canada announced the findings from his year-long investigation into two projects undertaken by Statistics Canada that were designed to access Canadians' financial microdata through banks and credit rating agencies.

The investigation found that Statistics Canada complied with the spirit and intent of both the Statistics Act and the Privacy Act, but recommended that the future versions of the two projects take into account the necessity (i.e., need and justification) of the data being collected and the proportionality (i.e., appropriate magnitude of the effort as it relates to the need) of the sample being designed.

After strong collaboration with the Office of the Privacy Commissioner, Statistics Canada has become a global leader in its implementation of a ground-breaking Necessity and Proportionality Framework. This framework ensures and demonstrates more transparency for Canadians about the agency's processes to protect the privacy and confidentiality of information.

The Necessity and Proportionality Framework was shared at the United Nations Statistical Commission by the Chief Statistician and the Privacy Commissioner of Canada. Statistics Canada continues to lead work in this area while sharing progress with Canadians through the Trust Centre on its website.

This framework allows for the evaluation of data proportionality and necessity, while simultaneously ensuring that statistical values—such as quality of information, the protection of personal information, and confidentiality—remain intact. The framework is now fully imbedded into the data acquisition process and fully integrated in the privacy impact assessment process.

Canadians, businesses and associations are now assured that the information gathered by Statistics Canada has been obtained in a fully transparent and ethical manner. Also, by enabling the appropriate acquisition of data from a variety of data sources, the framework provides stakeholders with access to more precise and timely information for use in public policy-making and business decision-making that benefits all Canadians.

Building statistical capacity and fostering data literacy

In 2019–20, the agency led a series of external engagement and co-creation initiatives with public and private sector partners to build data literacy and promote data-driven decision-making. This involved welcoming partners from more than 25 federal departments and agencies, provincial and municipal governments, academia, the private sector, and civil society to participate in innovation hackathons on high-profile topics including the Sustainable Development Goals, early learning and child care, urban transit, empowering citizen science, food security, and workplace mental health measurement. The agency, through its regional services areas, provided training courses that helped users understand the use of data.

More specifically, Statistics Canada has made important contributions in building statistical capacity and fostering data in specific subject matter areas, including Indigenous statistics, and gender, diversity and inclusion data. The agency also showed leadership in the development of both the federal data strategy and its own data strategy.

Supporting Indigenous communities with statistics

As part of the Indigenous Statistical Capacity Development Initiative, the Centre for Indigenous Statistics and Partnerships engaged with over 127 Indigenous communities, organizations and governments and successfully completed three pilot projects, which included training Apatisiiwin Skills Development (formerly the Cree Human Resources Development Office) to design, collect, process and analyze a survey in 10 communities. This led to a three-year plan to develop and deliver 15 courses to help Indigenous communities and organizations build their own data and research capacities.

The agency released three publications as part of a comprehensive release strategy that encompassed three booklets, three infographics and one interactive map. The analytical publications focused on employment among First Nations people living off reserve, and Métis and Inuit participation in the wage and land-based economies in Inuit Nunangat.

In 2019–20, the agency developed indexes, indicators and portals to address the statistical needs of Indigenous communities, organizations and leadership.

Key products included

• Indigenous life expectancy for the human development index
• new indicators and analyses related to the over-representation of Indigenous people in the criminal justice system
• the Indigenous Statistics Portal, which was launched on National Indigenous Peoples Day (June 21, 2019).

To address data gaps, the agency calculated school participation rates for children aged 4 to 6 living on reserve by using administrative data from Indigenous Services Canada.

Leading the way: Gender, diversity and inclusion statistics

Statistics Canada is not only on the leading edge of new technologies, but also at the vanguard of efforts to address data gaps to help Canadians get the necessary information to make important decisions. The Centre for Gender, Diversity and Inclusion Statistics (CGDIS) is an example of a Statistics Canada initiative that focuses on providing new information to Canadians and building statistical capacity.

For instance, in 2019–20, the CGDIS released 19 tables on the Gender, Diversity and Inclusion Statistics Hub in support of the Gender Results Framework. In addition, a new publication to publish gender-based analysis plus (GBA+) articles was created. The CGDIS also published a conceptual and methodological overview of the gender pay gap and published a number of articles and infographics to address key policy needs and raise awareness of issues related to gender, diversity and inclusion.

Positive feedback from data users was received for four products that specifically highlighted new disaggregated data on Black communities in Canada, with a focus for policy departments to identify the socioeconomic issues facing Black communities in Canada. Statistics Canada released a socioeconomic portrait of Canada's Black population in February 2020 to support the Government of Canada's priority to address socioeconomic issues faced by Black Canadians.

In 2019–20, the CGDIS continued to generate new information to improve statistical standards for GBA+. Statistics Canada developed the capacity to acquire data from other departments that can be "housed" at Statistics Canada to help measure progress on the Gender Results Framework indicators. For example, data from the Band Governance Management System were acquired with Crown–Indigenous Relations and Northern Affairs Canada to develop indicators on the gender composition of First Nations band councils and the proportion of Chiefs in First Nations communities who are women. In addition, work is being undertaken in collecting and disseminating ethnocultural statistics. With support from Canadian Heritage, the new cycle of the General Social Survey on Social Identity will allow for the disaggregation of some specific ethnocultural groups to help address issues related to anti-racism, such as discrimination.

Finally, 2019–20 saw the continued building of statistical capacity for the CGDIS. It worked closely with the Canada School of Public Service to develop training materials and to deliver a GBA+ premium course. The CGDIS reviews course content annually, sits on discussion panels, and co-presents the module Geeking out About Data, which guides participants through selecting a data source, disaggregating data and interpreting results using a GBA+ perspective. The CGDIS also released the results from the Survey of Safety in Public and Private Spaces. These results helped to expand knowledge on gender-based violence among the general population in a new way by including a wider range of behaviours that are on the continuum of gender-based violence, but may not necessarily meet the criminal threshold.

Data strategies for the federal public service and Statistics Canada

In 2019–20, work was undertaken to deliver three high-priority initiatives in support of the government-wide implementation of the Data Strategy Roadmap for the Federal Public Service.

• The Data Literacy and Training initiative will provide online, user-centric training videos to build capacity among public servants so that they can better understand and use Statistics Canada's data to make evidence-based decisions and policies.
• The Data Stewardship as a Service initiative involves partnerships with Government of Canada organizations to increase their capacity to manage and mobilize data, including through the use of standards. Statistics Canada and Employment and Social Development Canada launched a pilot project using address data to demonstrate the potential of all federal departments using one authoritative source of information for addresses rather than duplicating efforts.
• The Data Science Community initiative involves building a data science ecosystem to share expertise and best practices to build data science capacity across the federal government.

Statistics Canada also collaborated with the Canada School of Public Service (CSPS) to pilot an approach to measure data literacy, and engaged with other departments such as Innovation, Science and Economic Development Canada, Employment and Social Development Canada, the Privy Council Office, the Canadian Northern Economic Development Agency and Global Affairs Canada to discuss scaling beyond the agency. Support was provided on a number of other CSPS initiatives: establishing data literacy competencies, guiding the development of the "Discover Data" training course, and contributing to the CSPS data literacy training project to produce online training resources in core data literacy areas (e.g., quality, stewardship, analysis).

The Statistics Canada Data Strategy (SCDS) was released internally to the federal public service in late September 2019 and publicly in late April 2020. The SCDS provides a roadmap for how Statistics Canada will continue to govern and manage its valuable data assets as part of its modernization agenda and in alignment with and response to other federal government strategies and initiatives, including the Data Strategy Roadmap for the Federal Public Service, Canada's 2018–2020 National Action Plan on Open Government, and the Treasury Board Secretariat Digital Operations Strategic Plan: 2018–2022.

In a related project, Statistics Canada is leading the implementation of a proof-of-concept external data stewardship engagement office. With the end goal of building capacity and fostering data literacy, this office will directly engage with other federal departments and agencies to optimize the use of data to facilitate sharing and integration, reduce duplication, and increase trust and transparency.

Results achieved

Across the agency, employees are working to improve results and to ensure targets are both relevant and ambitious. The agency made significant progress and reached 7 out of 11 performance indicator targets for 2019–20, and has improved its results relative to previous years. As the Departmental Results Framework matures, the agency is integrating performance indicator results into its decision-making processes to ensure value for Canadians and alignment of resources with government priorities.

Results achieved

Departmental results	Performance indicators	Target	Date to achieve target	2017–18 Actual results	2018–19 Actual results	2019–20 Actual results
Statistical information is of high quality	Number of post-release corrections due to accuracy	0	March 31, 2020	3	2	1
	Number of international forums of which Statistics Canada is a member	170 to 190	March 31, 2020	168	184	190
	Percentage of international standards with which Statistics Canada conforms	90%Table note 1	March 31, 2020	89%	88%	88%Table note 2
Statistical information is available and accessed	Number of visits to Statistics Canada website	17,000,000Table note 3	March 31, 2020	26,461,926	19,752,776Table note 4	20,285,269Table note 5
	Percentage of website visitors that found what they were looking for	77%	March 31, 2020	76%	79%	78%
	Number of interactions on social media	400,000Table note 6	March 31, 2020	559,709	358,673Table note 7	521,441Table note 8,Table note 9
	Number of statistical products available on the website	37,300	March 31, 2020	33,642	35,920	37,254
	Number of Statistics Canada data tables available on the Open Data Portal	7,150	March 31, 2020	7,162	6,944Table note 10	7,386
Statistical information is relevant	Number of media citations on Statistics Canada data	70,000	March 31, 2020	67,539	74,657Table note 11	56,921Table note 12
	Number of journal citations	23,000	March 31, 2020	23,903	22,716	26,505Table note 13
	Percentage of users satisfied with statistical information	80%	March 31, 2020	79%	80%	80%
Footnote 1 The target is set at 90% since not all international standards are relevant to Statistics Canada. Return to footnote 1 referrer Footnote 2 While the results have remained the same from last year, the agency's overall trend is increasing toward greater use of standards. Five additional standards were in scope in 2019–2020, of which four were in use, resulting in the department level staying constant at 88%. Return to footnote 2 referrer Footnote 3 The target for 2019–20 reflects the change in software that calculates this indicator, from Webtrends to Adobe Analytics, in June 2018. Adobe Analytics is a Government of Canada solution that aims to provide better-quality data by removing traffic generated from identified robots, spiders and crawlers. The definition of a visit has also changed from "a series of pages viewed within 30 minutes" to "a visit begins when a visitor enters the site and ends within 30 minutes of inactivity or 12 continuous hours of activity." Based on the change of software and definition of a visit, the number of visits to the website is expected to decrease. The data for this indicator will no longer be comparable with previous years. Return to footnote 3 referrer Footnote 4 Statistics Canada changed the software for measuring website traffic in September 2018 from a technology based on log files to a modernized page-tag technology. This solution was chosen by the Government of Canada to provide better-quality data and remove non-human traffic. The actual number of total visits provided for 2018–19 is a combination of data derived from the old and new technologies, and is lower than the target of 24,000,000 previously provided because of the change in methodology. Because of the change in technology, the 2018–19 results cannot be compared with results from previous years. Return to footnote 4 referrer Footnote 5 Statistics Canada exceeded its target as there was an increase in the number of tables released in 2019–20 compared with previous years, and the 2019 Canadian election campaign caused an increase in visitors looking for information on the Canadian economy. Return to footnote 5 referrer Footnote 6 Results peaked from 2015 to 2018 because of Census Program activities and paid advertising related to the census. Since the beginning of 2018, some social media platforms have been using new methodologies to tailor content delivery to fewer audience members. The target for 2019–20 has been lowered in consideration of these two factors. Return to footnote 6 referrer Footnote 7 Fiscal year 2018–19 had the lowest interaction on social media in the census cycle. Furthermore, since the beginning of 2018, some social media platforms have been using new methodologies to tailor content delivery to fewer audience members. The target for 2019–20 has been lowered in consideration of these two factors. Return to footnote 7 referrer Footnote 8 Statistics Canada had more interactions on social media as significant efforts were made during fiscal year 2019–20 to increase visibility of the agency’s social media content and leverage partnerships with other government departments and key stakeholders for amplification. These actions helped boost overall interactions on the social media accounts above projected targets. Return to footnote 8 referrer Footnote 9 An updated methodology is being considered for this indicator to standardize and include new social media platforms that the agency uses to interact with Canadians. This new methodology would be introduced in future Departmental Plans and applied as a correction to the 2020–21 Departmental Plan. Return to footnote 9 referrer Footnote 10 The number of datasets was streamlined in 2018–19 as a result of the agency’s New Dissemination Model. While this has decreased the number of datasets on the Open Data Portal, it has resulted in a more simplified, coherent and user-friendly approach to accessing statistical information. Return to footnote 10 referrer Footnote 11 The target for 2018–19 was exceeded. Beginning in October 2018, a single significant media story about Statistics Canada contributed to a significant one-time boost of about 2,000 articles in the first six months. However, broad increases to four themes—economy (3,853), health (1,875), justice (1,771) and trade (1,740)—resulted in an additional 9,239 media citations. This made up for the dip in citations from the census and contributed to exceeding the target of 56,000 provided for 2018–19. Leading up to and following the legalization of recreational cannabis, media afforded considerable coverage to the agency’s economic and health releases. International trade issues and heightened interest in justice issues also captured media attention. Media citations for future years could continue to increase as coverage shifts to the growing number of Internet news sites that the agency can access. Return to footnote 11 referrer Footnote 12 Statistics Canada media citations are generated from the publication of data released through the agency’s official channel, The Daily, and through responses to media inquiries and interviews. During the 2019–20 period, the national general election dominated much of the daily news coverage and the deployment of the Government of Canada’s caretaker convention, which restricts activities of government departments, reduced the agency’s data publishing and promotion activities. For these reasons, there were fewer media citations during this period than anticipated. Return to footnote 12 referrer Footnote 13 Statistics Canada had more journal citations for fiscal year 2019–20 as the number of current authors tracked through the collection tool (Google Scholar) increased. There were also a few articles that gathered an unusually high number of citations, which contributed to exceeding the target. Return to footnote 13 referrer

Budgetary financial resources (dollars)

	2019–20 Main Estimates	2019–20 Planned spending	2019–20 Total authorities available for use	2019–20 Actual spending (authorities used)	2019–20 Difference (Actual spending minus Planned spending)
Gross Expenditures	551,104,432	551,104,432	600,534,042	584,770,894	33,666,462
Respendable Revenue	-120,000,000	-120,000,000	-120,038,495	-120,038,495	-38,495
Net Expenditures	431,104,432	431,104,432	480,495,547	464,732,399	33,627,967

Human resources (full-time equivalents)

	2019–20 Planned full-time equivalents	2019–20 Actual full-time equivalents	2019–20 Difference (Actual full-time equivalents minus Planned full-time equivalents)
Gross expenditures	5,501	5,595	94
Respendable Revenue	-1,321	-1,366	-44
Net Expenditures	4,180	4,229	50

The difference between planned spending and actual spending is the result of an increase in resources for new initiatives from Budget 2018 & 2019. These initiatives include the New Anti-racism strategy, implementing a "Data Analytics as a Service" platform, co-developing an Indigenous Statistical Capacity Development Initiative, and enhancing GBA+ analysis through the creation of a Centre for Gender, Diversity and Inclusion Statistics.

The difference is also attributable to retroactive pay from the ratification of new collective agreements and budget carried forward from 2018–19 to 2019–20, allowing the agency to meet the needs of its cyclical programs and to invest in its integrated strategic planning process.

Furthermore, full-time equivalents vary slightly as a result of differences between the actual salary rates paid and the estimated average salary rates used to forecast planned spending.

Financial, human resources and performance information for Statistics Canada’s Program Inventory is available in GC InfoBase.

Internal Services

Description

Internal Services are those groups of related activities and resources that the federal government considers to be services in support of programs and/or required to meet corporate obligations of an organization. Internal Services refers to the activities and resources of the 10 distinct service categories that support program delivery in the organization, regardless of the Internal Services delivery model in a department. The 10 service categories are

• Acquisition Management Services
• Communication Services
• Financial Management Services
• Human Resources Management Services
• Information Management Services
• Information Technology Services
• Legal Services
• Material Management Services
• Management and Oversight Services
• Real Property Management Services.

Results

All Internal Services have been engaged with the agency's modernization agenda and have become more efficient and user-centric. Internal Services strengthened and modernized the agency's governance, performance management and risk management frameworks to support compliance and ensure the agency is efficiently aligning its resources.

Efficiencies and improvements have been made by leveraging technology, monitoring business processes and measuring performance. The agency increased data analytics within its Internal Services to provide quick and direct insight into the health of the organization.

Adapting to transformation

The modernization agenda is a significant transformation. Statistics Canada continues its proactive approach to monitor the agency's health through change, to identify trends in areas such as turnover, sick leave, job satisfaction and morale, and to take action to improve these trends.

The agency envisions a diverse, inclusive, respectful and healthy workplace that is agile and resilient to change. To support this vision, the agency has focused on strategies to measure and support organizational health, is developing an organizational health framework/index and indicators, and is collecting important information through pulse surveys and focus groups.

Performance measurement and program management

In line with these efforts, Statistics Canada continued to integrate performance measurement into program management and corporate planning to support and guide the agency's modernization journey. Specifically, performance measurement workshops were conducted with all program managers to develop a comprehensive agency logic model and measurement framework that aligns activities and outputs to outcomes. The resulting suite of indicators will allow the agency to better measure whether it is achieving its modernization agenda.

Internal Audit and Evaluation

To meet Canadians' need for timely and meaningful data, Statistics Canada's modernization agenda needed to ensure proper controls were in place to mitigate risk internally. In 2019–20, Internal Audit and Evaluation used results achieved and lessons learned to assure management that innovative and ongoing program delivery mitigated risks. These functions provided management with trusted and neutral information to inform decision making within the agency.

Diversity and inclusion

Throughout 2019–20, the Employee Equity, Diversity and Inclusion team conducted many activities and awareness campaigns to increase the visibility and effectiveness of resources available to all Statistics Canada employees. For example, tools and initiatives—including the Integrity and Respect hotline, access to appointed Integrity and Respect Awareness Officers, and promotion of the Employee Assistance Program and Informal Conflict Management Services—have been implemented within the agency. In addition, a multitude of training opportunities and discussion forums have been promoted to help employees broaden their perspectives and create a more inclusive environment.

Statistics Canada launched two action plans to support a culture of diversity and inclusion. The first was the 2019–20 Employment Equity and Diversity Action Plan, which identified three key achievements: a data-driven approach to diversity and inclusion, the elimination and prevention of representation gaps, and a work environment where all employees feel included. Key action items included mandatory staff training, tracking and identifying statistical trends in representation and progression of employment equity groups, monitoring Statistics Canada's diversity compared with Canadian society, and reviewing assessment tools by the Employment Equity and Diversity Section. The second action plan released was the Integrity and Respect Action Plan. Both of these plans were published as communication tools available to employees and illustrated organizational commitments and accountabilities.

Leveraging data analytics

Internal Services enable partners across the agency to make strategic management decisions—supported by data—that are related to human resources, financial management, procurement, accommodations, informatics services and more. A number of new trailblazing projects demonstrate the expansion of data analytics with a user-centric approach within the agency.

• To eliminate the need for ad hoc reports and to encourage proactive planning, the Human Resources Analytics Management Dashboard was created to provide a self-serve compilation of easy-to-use, interactive, visuals-based reports—composed of real-time data—on the agency's workforce.
• Pulse surveys—short questionnaires to help answer important, ad hoc managerial questions in a timely manner—were developed and analyzed.
• As the agency's migration to the cloud progresses, live consumption metrics and optimization have been implemented to ensure robust and efficient operations.
• The Financial Operations Analytics Dashboard was created to report on the health of key performance indicators and compliance with established Finance Branch service standards. This dynamic reporting tool allows the agency to identify potential risks and performance issues as it seeks to achieve continuous improvement and client satisfaction in the application of operational business processes.

A more modern and flexible work environment

The agency continues to move toward a more modern and flexible work environment through the development of open workspace concepts, additional network bandwidth, and remote work procedures, including mandatory employee training.

In addition, in partnership with Public Services and Procurement Canada, the agency launched the GCcoworking pilot. This pilot allows employees to use conveniently located workspaces outside the agency's main offices. This approach reduces the agency's carbon footprint, improves work–life balance and encourages collaboration.

Procurement initiatives

In support of modern comptrollership, procurement activities continue to be made more efficient and modern. This included reducing manual processes (electronic submission and acceptance) and decentralizing the 2021 Census procurement process to a more efficient and regionally benefitting approach. Social and green procurement approaches included purchasing paper with at least 30% recycled content and using Indigenous vendors for IT equipment and furniture. Similarly, furniture was purchased from CORCAN, which provides employment and employability skills training to incarcerated offenders.

Further strengthening information management

The agency established a renewed information management vision, with foundational principles and alignment to internationally recognized frameworks, to drive key business outcomes. This project is moving forward to deliver key information and data capabilities to meet the needs of the modernization agenda and major program delivery.

Digital solutions

To provide full transparency into the agency's efficiency and modernization efforts, the agency launched its first IT Plan of Record. This report provides greater visibility to the IT-enabled investments within the agency. It transparently details all IT-enabled investments across projects, products and services. In addition, to streamline help desk costs, two separate walk-up services for employee support (the Genius bar and the Accounts Desk) were consolidated to create a single station that now provides a broader set of services and expanded service hours, while reducing costs.

Further focusing on IT operations and lifecycle management, Statistics Canada advanced its technological modernization agenda through a number of complex, large-scale informatics projects:

• The Cloud Services Enablement project aims to build the secure foundational blocks required to support current applications and data requirements, as well as the possibility of new cloud solutions.
• The Workload Migration project seeks to move current applications and datasets into a cloud environment as much as possible. In June 2019, Statistics Canada and the Treasury Board Secretariat began establishing the Government of Canada's first Workload Migration Factory.
• In 2019–20, the agency officially kicked off development for the Data Analytics as a Service (DAaaS) program. As the year progressed, DAaaS successfully delivered technical components and solutions in support of the agency's modernization vision and in support of the Data Strategy Roadmap for the Federal Public Service.

Budgetary financial resources (dollars)

2019–20 Main Estimates	2019–20 Planned spending	2019–20 Total authorities available for use	2019–20 Actual spending (authorities used)	2019–20 Difference (Actual spending minus Planned spending)
64,345,374	64,345,374	82,048,294	82,217,225	17,871,851

Human resources (full-time equivalents)

2019–20 Planned full-time equivalents	2019–20 Actual full-time equivalents	2019–20 Difference (Actual full-time equivalents minus Planned full-time equivalents)
566	626	60

The difference between planned spending and actual spending is mainly related to an increase in resources for a new initiative, approved in 2018–19, to migrate the infrastructure to the cloud, as well as additional spending related to internal IT support and pressures related to the Government of Canada pay system.

Although additional expenditures were prioritized under Internal Services, the agency's overall spending did not exceed its total authorities.

Financial, human resources and performance information for Statistics Canada's Program Inventory is available in the GC InfoBase.

Results at a glance

	Total actual spending for 2019–20	Total actual full-time equivalents for 2019–20
Total gross expenditures	666,988,119	6,221
Respendable revenues	-120,038,495	-1,366
Total net expenditures	546,949,624	4,856

During 2019–20, Statistics Canada made significant progress toward its modernization goals, including its goals to engage with Canadians, share best practices and expertise, build capacity, and generate new, innovative solutions to help create a data-driven society and economy. The initiatives and projects featured in this report demonstrate the impact that the agency has had on the lives of Canadians.

Creating a modern and flexible workplace

In response to the COVID-19 pandemic, the agency transitioned to a remote workplace overnight—a feat only possible because of in-flight modernization activities.

• Ongoing security and informatics enhancements for remote work allowed the agency to deliver its mission-critical programs, such as the Labour Force Survey, when they were most needed without missing a beat.
• Parallel to technical enhancements, a corporate culture change was initiated during 2019–20 toward a more agile, flexible and responsive organization.

Delivering user-centric services

The agency is client-focused; it wants to ensure that users have the information they want when they want it and how they want it.

• Canadians asked for more data visualizations, such as user-friendly online interactive tools and fun infographics, and the agency responded. In 2019–20 alone, the agency doubled its number of data visualization tools and increased its infographics holdings by 35%. Users also wanted more social media activity—there were over 520,000 social media interactions in 2019–20.
• User satisfaction results revealed that, in 2019–20, 80% of users were satisfied with the statistical information provided by Statistics Canada, including with the over 38,000 products that were accessed in approximately 20.3 million visits to the agency's website.

Collaborating and engaging with Canadians

This past year, Statistics Canada pursued an unprecedented number of collaborative activities and initiatives across all levels of government; internationally; and with the private sector, non-governmental organizations and others.

• In the summer of 2019, the agency demonstrated its commitment to collaboration and engagement by creating a new corporate Strategic Engagement Field, dedicated to meeting the statistical needs of Canadians. Collaboration and engagement activities resulted in more granular and timely data related to housing, tourism, justice, health and manufacturing, to name a few.
• To foster increased collaboration with other organizations, many speeches and special outreach and engagement events occurred. Specific external audiences included the Empire Club, the Canadian Chamber of Commerce, the Federation of Canadian Municipalities, and the Canadian Association of Chiefs of Police. The agency also collaborated with international partners; for example, the agency was a member of 180 international forums in 2019–20.
• The Canadian Statistics Advisory Council (CSAC)—the independent body comprised of statistical experts from across the country mandated to report to Canadians annually on the overall health of the national statistical system—met for the first time in 2019–20.

Using leading-edge methods

The agency's modernization journey paved the way for work on leading-edge methods. Canadians and businesses want detailed, high-quality, real-time statistical information, and the agency is committed to using innovative methods to meet these increasing data needs.

• Statistics Canada continued to produce more data while reducing the response burden on Canadians through new projects, including producing cannabis consumption data based on wastewater and using satellite imagery to replace some agriculture surveys.
• Statistics Canada presented leading-edge methods on a global scale regarding its implementation of the Necessity and Proportionality Framework. The framework ensures and demonstrates transparency about the agency's processes to protect privacy and confidentiality by ensuring that all projects meet a real need (necessity) and are of an appropriate magnitude or size of effort (proportionality).

Building statistical capacity and fostering data literacy

For a data-driven society and economy, society must understand and use statistics. To help build statistical capacity with partners and foster data literacy among Canadians so they can effectively use the agency's data, Statistics Canada provided leadership nationally and internationally.

• In 2019–20, the agency supported the government-wide implementation of the Data Strategy Roadmap for the Federal Public Service and released its own Statistics Canada Data Strategy to outline how the agency will continue to govern and manage its valuable data assets for Canadians.
• Statistics Canada provided direct support and training to over 127 Indigenous communities, organizations and governments to help them build their own data and research capabilities, including developing indexes, indicators and portals to address their specialized statistical needs.
• With over 5,875 participants in 2019–20, Statistics Canada's workshop and webinar series improved data literacy by providing Canadians with direct access to its extensive survey methodology and analysis expertise.

As the impacts of COVID-19 continue to be felt, Statistics Canada continues to capture an accurate social and economic portrait of the nation and provide Canadians with the information they need to make important decisions during these extraordinary times. The agency also accelerated the collection and release of COVID-19-related information to create new insights that are urgently needed to respond to and address the COVID-19 pandemic.

For more information on Statistics Canada's plans, priorities and results achieved, see the "Results: what we achieved" section of this report.

It is a pleasure to outline Statistics Canada's accomplishments over the 2019–20 fiscal year in this Departmental Results Report. In 2019–20, the agency experienced unprecedented change and further opportunity to serve Canadians with credible, trusted and quality data and insights.

COVID-19 fuelled an extraordinary demand for a better understanding of Canada's society and economy in more granular detail, near real-time and in an integrated manner. Leveraging the agency's modernization efforts that were already underway, Statistics Canada's dedicated and committed experts securely transitioned to remote work practically overnight, and transformed many of the agency's programs to bring greater value to decision makers.

In addition to providing key statistics that drive Canada's economy and society, Statistics Canada is using good data management and stewardship practices to track the impacts of COVID-19 and to help Canada to better manage critical resources, such as personal protective equipment inventories. The agency has introduced new collection mechanisms and new methodologies by working in partnership with other departments to bring disaggregated data and new insights to Canadians in a timely manner. I thank Canadians for their remarkable support in helping the agency in its efforts. Their support showed how much Canadians value the agency's high-quality evidence and data, which help to influence decisions that impact all of Canada.

Statistics Canada is grateful for the advice and guidance of the members of the newly formed Canadian Statistics Advisory Council, as well as the Advisory Council on Ethics and Modernization of Microdata Access, provincial and territorial statistical focal points, numerous subject matter and technical advisory committees, and international colleagues.

Although more work is needed, the agency is making important strides in supporting key government priorities such as gender, diversity and inclusion, physical and mental health, energy statistics, the environment, and sustainable growth. Statistics Canada is also working to meet the increasing dependence on data to fuel Canada's economy and jobs, and is working to support building statistical capacity in Indigenous organizations.

The agency is also grateful to organizations and Canadians who participated in this past year's content consultations for the 2021 Census of Population and Census of Agriculture. The input received will help to ensure next year's censuses provide the solid evidence base needed for years to come.

Statistics Canada has operated in a transparent manner for over a century, earning the trust of Canadians. The agency is sharing even more information about what it does and how it goes about providing high-quality statistics. I invite Canadians to visit Statistics Canada's Trust Centre to learn more about how the agency works for them. I also invite Canadians to get to know the agency's dedicated employees in our video series, Faces of StatCan.

Canadians look to Statistics Canada to provide independent, credible and trusted information at a time when it can be challenging to differentiate information quality. I invite all Canadians, businesses and organizations to explore the agency's resources, which include dashboards, hubs and portals, releases in The Daily, data repositories, and hundreds of analytical papers. All these resources are available for free on the Statistics Canada website.

Statistics Canada is grateful for your support and trust, and the agency looks forward to continuing to serve you by delivering even greater insights through data for a better Canada.

Anil Arora
Chief Statistician of Canada

Summaries of disseminated products

Dissemination Plan

CHMS Content summary for cycles 1 to 8

• The content summary document is divided into separate tables which list all of the content topics in the survey by age group of respondent. There are tables on the household questionnaire and specimen collection, mobile examination centre (MEC) physical measures and specimen collection, MEC questionnaire, laboratory biospecimen, laboratory indoor air sample tests and laboratory tap water sample tests. The laboratory tables also provide information on analytical ranges and conversion factors.

Data User Guide – Cycles 1 to 6

• The user guide includes information on survey content, sample design, data collection, data processing, weighting, data quality, file usage, as well as guidelines for tabulation, analysis and release.
• Cycle 6 release to start October 2020

Derived Variables (DVs) documentation – Cycles 1 to 6

• There are separate DV documents for the following types of DVs: household and mobile examination centre (MEC), medication, activity monitor, non-environmental laboratory measures, fluoride and volatile organic compounds, and other environmental laboratory measures.
• Cycle 6 release to start October 2020

Data Dictionaries – Cycles 1 to 6

• There are separate data dictionaries for the following data files: household full sample, mobile examination centre full sample, medication full sample, hearing full sample, activity monitor full sample, activity monitor subsample, indoor air subsample – household level, indoor air subsample – person level, fasting blood subsample, red blood cell fatty acids subsample, fluoride household level subsample – in tap water, VOC household level subsample – in tap water, fluoride person level subsample – in urine and tap water, VOC person level subsample – in blood and tap water, non-environmental lab data full sample, environment lab blood and urine full sample, acrylamide (environmental blood subsample), methyl mercury (environmental blood subsample), NNAL and glucoronides (environmental urine subsample), and environment urine main subsample. Note: not all subsamples are available in every cycle
• Cycle 6 release to start October 2020

Supporting documentation for the climate and air quality file – Cycle 3
Sampling Documentation – Cycle 1 to 5
Presentations on using CHMS data – Cycles 1 to 5

• CHMS Data User Workshop

Instructions for Combining Multiple Cycles of Canadian Health Measures Survey (CHMS) Data
Postal Code File – justification needed

• Contains postal code information for every respondent in the survey.

Relationship File – justification needed

• Identifies the relationship between 2 respondents in the same household (adult/child)

Relationship File – Feasibility Report

• Using the relationship files and paired respondent data in the CHMS: Feasibility study – an update

CHMS Errata – Cycles 1 to 6

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For more information or to obtain copies of the documents in the list above, please contact Statistics Canada's Statistical Information Service (toll-free 1-800-263-1136; 514-283-8300; infostats@statcan.gc.ca).

1.0 Description

The Canadian Perspectives Survey Series (CPSS) is a set of short, online surveys beginning in March 2020 that will be used to collect information on the knowledge and behaviours of residents of the 10 Canadian provinces. All surveys in the series will be asked of Statistics Canada's probability panel. The probability panel for the CPSS is a new pilot project initiated in 2019. An important goal of the CPSS is to directly collect data from Canadians in a timely manner in order to inform policy makers and be responsive to emerging data needs. The CPSS is designed to produce data at a national level (excluding the territories).

The survey program is sponsored by Statistics Canada. Each survey in the CPSS is cross sectional. Participating in the probability panel and the subsequent surveys of the CPSS is voluntary.

The fifth survey of the CPSS is CPSS5 – Technology Use and Cyber Security during the Pandemic. It was administered from September 14, 2020 until September 20, 2020.

Any questions about the survey, the survey series, the data or its use should be directed to:

Statistics Canada

Client Services
Centre for Social Data Integration and Development
Telephone: 613-951-3321 or call toll-free 1-800-461-9050
Fax: 613-951-4527
E-mail: statcan.csdidclientservice-ciddsservicealaclientele.statcan@statcan.gc.ca

2.0 Survey methodology

Target and survey population

The target population for the Canadian Perspectives Survey Series (CPSS) is residents of the 10 Canadian provinces 15 years of age or older.

The frame for surveys of the CPSS is Statistics Canada's pilot probability panel. The probability panel was created by randomly selecting a subset of the Labour Force Survey (LFS) respondents. Therefore the survey population is that of the LFS, with the exception that full-time members of the Canadian Armed Forces are included. Excluded from the survey's coverage are: persons living on reserves and other Aboriginal settlements in the provinces; the institutionalized population, and households in extremely remote areas with very low population density. These groups together represent an exclusion of less than 2% of the Canadian population aged 15 and over.

The LFS sample is drawn from an area frame and is based on a stratified, multi-stage design that uses probability sampling. The LFS uses a rotating panel sample design. In the provinces, selected dwellings remain in the LFS sample for six consecutive months. Each month about one-sixth of the LFS sampled dwellings are in their first month of the survey, one-sixth are in their second month of the survey, and so on. These six independent samples are called rotation groups.

For the probability panel used for the CPSS, four rotation groups from the LFS were used from the provinces: the rotation groups answering the LFS for the last time in April, May, June and July of 2019. From these households, one person aged 15+ was selected at random to participate in the CPSS - Sign-Up. These individuals were invited to Sign-Up for the CPSS. Those agreeing to join the CPSS were asked to provide an email address. Participants from the Sign-Up that provided valid email addresses formed the probability panel. The participation rate for the panel was approximately 23%. The survey population for all surveys of the CPSS is the probability panel participants. Participants of the panel are 15 years or older as of July 31, 2019.

Sample Design and Size

The sample design for surveys of the CPSS is based on the sample design of the CPSS – Sign-Up, the method used to create the pilot probability panel. The raw sample for the CPSS – Sign-Up had 31,896 randomly selected people aged 15+ from responding LFS households completing their last interview of the LFS in April to July of 2019. Of these people, 31,626 were in-scope at the time of collection for the CPSS - Sign-Up in January to March 2020. Of people agreeing to participate in the CPSS, that is, those joining the panel, 7,242 had a valid email address. All panel participants are invited to complete the surveys of the CPSS.

Stages of the Sample	n
Raw sample for the CPSS – Sign-Up	31,896
In-scope Units from the CPSS – Sign-Up	31,628
Panelists for the CPSS (with valid email addresses)	7,242
Raw sample for surveys of the CPSS	7,242

3.0 Data collection

CPSS – Sign-Up

The CPSS- Sign-Up survey used to create Statistics Canada's probability panel was conducted from January 15th, 2020 until March 15th, 2020. Initial contact was made through a mailed letter to the selected sample. The letter explained the purpose of the CPSS and invited respondents to go online, using their Secure Access Code to complete the Sign-Up form. Respondents opting out of joining the panel were asked their main reason for not participating. Those joining the panel were asked to verify basic demographic information and to provide a valid email address. Nonresponse follow-up for the CPSS-Sign-Up had a mixed mode approach. Additional mailed reminders were sent to encourage sampled people to respond. As well, email reminders (where an email address was available) and Computer Assisted Telephone Interview (CATI) nonresponse follow-up was conducted.

The application included a standard set of response codes to identify all possible outcomes. The application was tested prior to use to ensure that only valid question responses could be entered and that all question flows would be correctly followed. These measures ensured that the response data were already "clean" at the end of the collection process.

Interviewers followed a standard approach used for many StatCan surveys in order to introduce the agency. Selected persons were told that their participation in the survey was voluntary, and that their information would remain strictly confidential.

CPSS5 – Technology Use and Cyber Security during the Pandemic

All participants of the pilot panel for the CPSS, minus those who opted out after previous iterations of CPSS, were sent an email invitation with a link to the CPSS5 and a Secure Access Code to complete the survey online. Collection for the survey began on September 14th, 2020. Reminder emails were sent on September 15, September 17 and September 19. On September 17 in the afternoon, SMS reminders were sent (where a phone number was available) to sampled people aged 18 to 24 to encourage them to respond. The application remained open until September 20, 2020.

3.1 Disclosure control

Statistics Canada is prohibited by law from releasing any data which would divulge information obtained under the Statistics Act that relates to any identifiable person, business or organization without the prior knowledge or the consent in writing of that person, business or organization. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.

4.0 Data quality

Survey errors come from a variety of different sources. They can be classified into two main categories: non-sampling errors and sampling errors.

4.1 Non-sampling errors

Non-sampling errors can be defined as errors arising during the course of virtually all survey activities, apart from sampling. They are present in both sample surveys and censuses (unlike sampling error, which is only present in sample surveys). Non-sampling errors arise primarily from the following sources: nonresponse, coverage, measurement and processing.

4.1.1 Nonresponse

Nonresponse errors result from a failure to collect complete information on all units in the selected sample.

Nonresponse produces errors in the survey estimates in two ways. Firstly, non-respondents often have different characteristics from respondents, which can result in biased survey estimates if nonresponse bias is not fully corrected through weighting. Secondly, it reduces the effective size of the sample, since fewer units than expected answered the survey. As a result, the sampling variance increases and the precision of the estimate decreases. The response rate is calculated as follows:

[ Responding units / (Selected units – out-of-scope units) ] x 100%

The following table summarizes the response rates experienced for the CPSS5 – Technology Use and Cyber Security during the Pandemic. Response rates are broken down into two stages. Table 4.1.1a shows the take-up rates to the panel in the CPSS- Sign-Up and Table 4.1.1b shows the collection response rates for the survey CPSS5 – Technology Use and Cyber Security during the Pandemic.

Table 4.1.1a Participation in the Pilot Probability Panel for the CPSS – Sign-Up

	Stages of the Sample for the CPSS – Sign-Up
	Raw sample for the CPSS – Sign-Up	In-scope Units from the CPSS – Sign-Up	Panelists for the CPSS (with valid email addresses)	Participation Rate for the Panel for CPSS
n	31,896	31,628	7,242	22.9%

Table 4.1.1b Response Rates to the CPSS5 – Technology Use and Cyber Security during the Pandemic

	Stages of the Sample for the CPSS5 – Technology Use and Cyber Security during the Pandemic
	Panelists for the CPSS (with valid email addresses)	Respondents of CPSS5 – Technology Use and Cyber Security during the Pandemic	Collection Response Rate for CPSS5 – Technology Use and Cyber Security during the Pandemic	Cumulative Response Rate
n	7,242	3,961	54.7%	12.5%

As shown in Table 4.1.1b, the collection response rate for the CPSS5 – Technology Use and Cyber Security during the Pandemic is 54.7%. However, when nonparticipation in the panel is factored in, the cumulative response rate to the survey is 12.5%. This cumulative response rate is lower than the typical response rates observed in social surveys conducted at Statistics Canada. This is due to the two stages of nonresponse (or participation) and other factors such as the single mode used for surveys of the CPSS (emailed survey invitations with a link to the survey for online self-completion), respondent fatigue from prior LFS response, the inability of the offline population to participate, etc.

Given the additional nonresponse experienced in the CPSS5 – Technology Use and Cyber Security during the Pandemic there is an increased risk of bias due to respondents being different than nonrespondents. For this reason, a small bias study was conducted. Please see Section 6.0 for the results of this validation.

4.1.2 Coverage errors

Coverage errors consist of omissions, erroneous inclusions, duplications and misclassifications of units in the survey frame. Since they affect every estimate produced by the survey, they are one of the most important types of error; in the case of a census they may be the main source of error. Coverage errors may cause a bias in the estimates and the effect can vary for different sub-groups of the population. This is a very difficult error to measure or quantify accurately.

For the CPSS, the population covered are those aged 15+ as of July 31, 2019. Since collection of the CPSS5 – Technology Use and Cyber Security during the Pandemic was conducted from September 14th-20th, 2020, there is an undercoverage of residents of the 10 provinces that turned 15 since July 31, 2019. There is also undercoverage of those without internet access. This undercoverage is greater amongst those age 65 years and older.

4.1.3 Measurement errors

Measurement errors (sometimes referred to as response errors) occur when the response provided differs from the real value; such errors may be attributable to the respondent, the questionnaire, the collection method or the respondent's record-keeping system. Such errors may be random or they may result in a systematic bias if they are not random. It is very costly to accurately measure the level of response error and very few surveys conduct a post-survey evaluation.

4.1.4 Processing errors

Processing errors are the errors associated with activities conducted once survey responses have been received. It includes all data handling activities after collection and prior to estimation. Like all other errors, they can be random in nature, and inflate the variance of the survey’s estimates, or systematic, and introduce bias. It is difficult to obtain direct measures of processing errors and their impact on data quality especially since they are mixed in with other types of errors (nonresponse, measurement and coverage).

4.2 Sampling errors

Sampling errors are defined as the errors that result from estimating a population characteristic by measuring a portion of the population rather than the entire population. For probability sample surveys, methods exist to calculate sampling error. These methods derive directly from the sample design and method of estimation used by the survey.

The most commonly used measure to quantify sampling error is sampling variance. Sampling variance measures the extent to which the estimate of a characteristic from different possible samples of the same size and the same design differ from one another. For sample designs that use probability sampling, the magnitude of an estimate's sampling variance can be estimated.

Factors affecting the magnitude of the sampling variance for a given sample size include:

1. The variability of the characteristic of interest in the population: the more variable the characteristic in the population, the larger the sampling variance.
2. The size of the population: in general, the size of the population only has an impact on the sampling variance for small to moderate sized populations.
3. The response rate: the sampling variance increases as the sample size decreases. Since non-respondents effectively decrease the size of the sample, nonresponse increases the sampling variance.
4. The sample design and method of estimation: some sample designs are more efficient than others in the sense that, for the same sample size and method of estimation, one design can lead to smaller sampling variance than another.

The standard error of an estimator is the square root of its sampling variance. This measure is easier to interpret since it provides an indication of sampling error using the same scale as the estimate whereas the variance is based on squared differences.

The coefficient of variation (CV) is a relative measure of the sampling error. It is defined as the estimate of the standard error divided by the estimate itself, usually expressed as a percentage (10% instead of 0.1). It is very useful for measuring and comparing the sampling error of quantitative variables with large positive values. However, it is not recommended for estimates such as proportions, estimates of change or differences, and variables that can have negative values.

It is considered a best practice at Statistics Canada to report the sampling error of an estimate through its 95% confidence interval. The 95% confidence interval of an estimate means that if the survey were repeated over and over again, then 95% of the time (or 19 times out of 20), the confidence interval would cover the true population value.

5.0 Weighting

The principle behind estimation in a probability sample such as those of the CPSS, is that each person in the sample "represents", besides himself or herself, several other persons not in the sample. For example, in a simple random 2% sample of the population, each person in the sample represents 50 persons in the population. In the terminology used here, it can be said that each person has a weight of 50.

The weighting phase is a step that calculates, for each person, his or her associated sampling weight. This weight appears on the microdata file, and must be used to derive estimates representative of the target population from the survey. For example, if the number of individuals who smoke daily is to be estimated, it is done by selecting the records referring to those individuals in the sample having that characteristic and summing the weights entered on those records. The weighting phase is a step which calculates, for each record, what this number is. This section provides the details of the method used to calculate sampling weights for the CPSS5 – Technology Use and Cyber Security during the Pandemic.

The weighting of the sample for the CPSS5 – Technology Use and Cyber Security during the Pandemic has multiple stages to reflect the stages of sampling, participation and response to get the final set of respondents. The following sections cover the weighting steps to first create the panel weights, then the weighting steps to create the survey weights for CPSS5 – Technology Use and Cyber Security during the Pandemic.

5.1 Creating the Panel Weights

Four consecutive rotate-out samples of households from the LFS were the starting point to form the panel sample of the CPSS. Since households selected from the LFS samples are the starting point, the household weights from the LFS are the first step to calculating the panel weights.

5.1.1 Household weights

Calculation of the Household Design Weights – HHLD_W0, HHLD_W1

The initial panel weights are the LFS subweights (SUBWT). These are the LFS design weights adjusted for nonresponse but not yet calibrated to population control totals. These weights form the household design weight for the panel survey (HHLD_W0).

Since only four rotate-outs were used, instead of the six used in a complete LFS sample, these weights were adjusted by a factor of 6/4 to be representative. The weights after this adjustment were called HHLD_W1.

Calibration of the Household Weights – HHLD_W2

Calibration is a step to ensure that the sum of weights within a certain domain match projected demographic totals. The SUBWT from the LFS are not calibrated, thus HHLD_W1 are also not calibrated. The next step is to make sure the household weights add up to the control totals by household size. Calibration was performed on HHLD_W1 to match control totals by province and household size using the size groupings of 1, 2, or 3+.

5.1.2 Person Panel weights

Calculate Person Design Weights – PERS_W0

One person aged 15 or older per household was selected for the CPSS – Sign-Up, the survey used to create the probability panel. The design person weight is obtained by multiplying HHLD_W2 by the number of eligible people in the dwelling (i.e. number of people aged 15 years and over).

Removal of Out of Scope Units – PERS_W1

Some units were identified as being out-of-scope during the CPSS – Sign-Up. These units were given a weight of PERS_W1 = 0. For all other units, PERS_W1 = PERS_W0. Persons with a weight of 0 are subsequently removed from future weight adjustments.

Nonresponse/Nonparticipation Adjustment – PERS_W2

During collection of the CPSS – Sign-Up, a certain proportion of sampled units inevitably resulted in nonresponse or nonparticipation in the panel. Weights of the nonresponding/nonparticipating units were redistributed to participating units. Units that did not participate in the panel had their weights redistributed to the participating units with similar characteristics within response homogeneity groups (RHGs).

Many variables from the LFS were available to build the RHG (such as employment status, education level, household composition) as well as information from the LFS collection process itself. The model was specified by province, as the variables chosen in the model could differ from one province to the other.

The following variables were kept in the final logistic regression model: education_lvl (education level variable with 10 categories), nameissueflag (a flag created to identify respondents not providing a valid name), elg_hhldsize (number of eligible people for selection in the household), age_grp (age group of the selected person), sex, kidsinhhld (an indicator to flag whether or not children are present in the household), marstat (marital status with 6 categories), cntrybth (an indicator if the respondent was born in Canada or not), lfsstat (labour force status of respondent with 3 categories), nocs1 (the first digit of National Occupational Classification code of the respondent if employed, with 10 categories), and dwelrent (an indicator of whether the respondent dwelling is owned or rented). RHGs were formed within provinces. An adjustment factor was calculated within each response group as follows:

$\frac{\text{Sum of weights of respondents and nonrespondents}}{\text{Sum of weights of respondents}}$

The weights of the respondents were multiplied by this factor to produce the PERS_W2 weights, adjusted for panel nonparticipation. The nonparticipating units were dropped from the panel.

5.2 Creating the CPSS5 weights

Surveys of the CPSS start with the sample created from the panel participants. The panel is comprised of 7,242 individuals, each with the nonresponse adjusted weight of PERS_W2.

Calculation of the Design Weights – WT_DSGN

The design weight is the person weight adjusted for nonresponse calculated for the panel participants (PERS_W2). No out-of-scope units were identified during the survey collection of CPSS5 – Technology Use and Cyber Security during the Pandemic. Since all units were in-scope, WT_DSGN =PERS_W2 and no units were dropped.

Nonresponse Adjustment – WT_NRA

Given that the sample for CPSS was formed by people having agreed to participate in a web panel, the response rates to the survey were relatively high. Additionally, the panel was designed to produce estimates at a national level, so sample sizes by province were not overly large. As a result, nonresponse was fairly uniform in many provinces. The RHGs were formed by some combination of age group, sex, education level, rental status, LFS status, whether or not children are present in the household, eligible household size, and the first digit of the National Occupational Classification (NOC) code for respondents who are employed. An adjustment factor was calculated within each response group as follows:

$\frac{\text{Sum of weights of respondents and nonrespondents}}{\text{Sum of weights of respondents}}$

The weights of the respondents were multiplied by this factor to produce the WT_NRA weights, adjusted for survey response. The nonresponding units were dropped from the survey.

Calibration of Person-Level Weights – WT_FINL

Control totals were computed using LFS demography projection data. During calibration, an adjustment factor is calculated and applied to the survey weights. This adjustment is made such that the weighted sums match the control totals. Most social surveys calibrate the person level weights to control totals by sex, age group and province. For CPSS5, calibration by province was not possible, since there were very few respondents in some categories in the Atlantic and Prairie Provinces. In addition, there were very small counts for male respondents aged 15 to 24 in the Atlantic Provinces. For this reason, the control totals used for CPSS5 – Technology Use and Cyber Security during the Pandemic were by age group and sex by geographic region, where the youngest age group for males in the Atlantic region, collapsed with the second youngest age group. The next section will include recommendations for analysis by geographic region and age group.

5.3  Bootstrap Weights

Bootstrap weights were created for the panel and the CPSS5 – Technology Use and Cyber Security during the Pandemic survey respondents. The LFS bootstrap weights were the initial weights and all weight adjustments applied to the survey weights were also applied to the bootstrap weights.

6.0 Quality of the CPSS and Survey Verifications

The probability panel created for the CPSS is a pilot project started in 2019 by Statistics Canada. While the panel offers the ability to collect data quickly, by leveraging a set of respondents that have previously agreed to participate in multiple short online surveys, and for whom an email address is available to expedite survey collection, some aspects of the CPSS design put the resulting data at a greater risk of bias. The participation rate for the panel is lower than typically experienced in social surveys conducted by Statistics Canada which increases the potential nonresponse bias. Furthermore, since the surveys of the CPSS are all self-complete online surveys, people without internet access do not have the means to participate in the CPSS and therefore are not covered.

When the unweighted panel was compared to the original sample targeted to join the panel, in particular there was an underrepresentation of those aged 15-24, those aged 65 and older, and those with less than a high school degree. These differences were expected due to the nature of the panel and the experience of international examples of probability panels. Using LFS responding households as the frame for the panel was by design in order to leverage the available LFS information to correct for the underrepresentation and overrepresentation experienced in the panel. The nonresponse adjustments performed in the weighting adjustments of the panel and the survey respondents utilised the available information to ensure the weights of nonresponding/nonparticipating units went to similar responding units. Furthermore, calibration to age and sex totals helped to adjust for the underrepresentation by age group.

Table 6.1 shows the slippage rates by certain domains post-calibration of CPSS5 – Technology Use and Cyber Security during the Pandemic. The slippage rate is calculated by comparing the sum of weights in the domain to that of the control total based off of demographic projections. A positive slippage rate means the sample has an over-count for that domain. A negative slippage rate means the survey has an under-count for that domain. Based on the results shown in Tables 6.1 and 6.2, it is recommended to only use the data at the geographical levels and age groups where there is no slippage. That is nationally, by geographic region (Maritime Provinces, Quebec, Ontario, Prairie Provinces, and British Columbia), and by the four oldest age groups.

Table 6.1 Slippage rates by geographic region

Area	Domain	n	Slippage Rate
Geography	CanadaFootnote 1	3,961	0%
	Newfoundland and Labrador	118	-7.3%
	Prince Edward Island	82	8.7%
	Nova Scotia	234	3.0%
	New Brunswick	174	-0.6%
	Quebec	664	0%
	Ontario	1,145	0%
	Manitoba	314	-3.7%
	Saskatchewan	273	7.4%
	Alberta	423	-0.8%
	British Columbia	534	0%
Footnote 1 Based on the 10 provinces; the territories are excluded Return to footnote 1 referrer

Table 6.2 Slippage rates by age group

Area	Domain	n	Slippage Rate
Age group	15-24	195	3.2%
	25-34	446	-2.7%
	35-44	643	0%
	45-54	624	0%
	55-64	925	0%
	65+	1,128	0%

After the collection of CPSS5 – Technology Use and Cyber Security during the Pandemic, a small study was conducted to assess the potential bias due to the lower response rates and the undercoverage of the population not online. The LFS data was used to produce weighted estimates for the in-scope sample targeted to join the probability panel (using the weights and sample from PERS_W1). The same data was used to produce weighted estimates based on the set of respondents from the CPSS5 survey and the weights WT_FINL. The two set of estimates were compared and are shown in Table 6.3. The significant differences are highlighted.

Table 6.3 Changes in estimates due to nonparticipation in the CPSS and the COVID-19 survey

Subject	Recoded variables from 2019 LFS	Estimate for in-scope population (n=31,628)	Estimate for W5 of CPSS (n=3,961)	% Point Difference
Education	Less than High SchoolTable 6.3 Footnote 11	15.5%	12.5%	2.9%
	High School no higher certification	25.9%	25.4%	0.5%
	Post-secondary certificationTable 6.3 Footnote 11	58.6%	62.0%	-3.4%
Labour Force Status	Employed	61.2%	62.7%	-1.5%
	Unemployed	3.4%	3.3%	0.1%
	Not in Labour Force	35.3%	34.0%	1.3%
Country of Birth	CanadaTable 6.3 Footnote 11	71.7%	76.2%	-4.5%
Marital Status	Married/Common-law	60.4%	61.2%	-0.8%
	Divorced, separated, widowed	12.8%	11.4%	1.3%
	Single, never married	26.9%	27.4%	-0.5%
Kids	Presence of childrenTable 6.3 Footnote 11	31.7%	34.6%	-2.9%
Household Size	Single person	14.4%	14.6%	-0.2%
	Two person HH	34.8%	36.4%	-1.6%
	Three or more people	18.4%	18.1%	0.2%
Eligible people for panel	One eligible person aged 15+	15.9%	16.1%	-0.2%
	Two eligible peopleTable 6.3 Footnote 11	49.3%	52.3%	-3.0%
	Three or more eligible peopleTable 6.3 Footnote 11	34.8%	31.7%	3.2%
Dwelling	Apartment	12.1%	12.0%	0.1%
	Rented	24.8%	24.9%	-0.1%
Occupational Code	Management occupations (NOC0)	6.0%	6.3%	-0.2%
	Business Finance and Administration (NOC1)	10.7%	11.2%	-0.5%
	Natural and Applied Sciences and related occupations (NOC2)Table 6.3 Footnote 11	5.2%	6.5%	-1.3%
	Health Occupations (NOC3)	4.7%	4.4%	0.4%
	Occupations in education, law and social, community and government services (NOC4)	7.6%	8.0%	-0.4%
	Occupations in art, culture, recreation and sports (NOC5)	2.5%	3.1%	-0.6%
	Sales and service occupations (NOC6)	16.6%	17.5%	-0.9%
	Trades, transport and equipment operators and related occupations (NOC7)	9.6%	9.3%	0.3%
	Natural resources, agriculture and related production occupations (NOC8)	1.6%	1.3%	0.4%
	Occupations in manufacturing and utilities (NOC9)	2.9%	2.3%	0.6%
Footnote 1 Estimates that are significantly different at α= 5%. Return to tablenote 1 referrer

While many estimates do not show significant change, the significant differences show that some bias remains in the CPSS5 – Technology Use and Cyber Security during the Pandemic. There is an underrepresentation of those where there were three or more eligible participants for the panel, and of people with less than a high school diploma. And there is an overrepresentation of those with a post-secondary certification, of people born in Canada, of people working in NOC2, of households where there were two eligible participants for the panel, and of households with children. These small differences should be kept in mind when using the CPSS5 – Technology Use and Cyber Security during the Pandemic survey data. Investigation about differences in estimates is ongoing, and as evidence of differences are identified, strategies are being tested to improve the methodology from one wave of the survey to the next.

Release date: November 5, 2020 Updated: September 21, 2021

The purpose of this notice is to advise all stakeholders and users of the National Occupational Classification (NOC) that the new 2021 classification's numbering system will be significantly modified as part of a major structural revision. The NOC 2021 is scheduled to be released in early 2021.

• Background
• Revising the NOC
• Impact on users
• Schedule A – NOC 2016
• Schedule B – NOC 2021

Background

Every ten years, the National Occupational Classification (NOC) undergoes a major structural revision whereby the existing occupational groups are reviewed alongside input collected from many relevant stakeholders through a consultation process. The NOC has been developed and is maintained as part of a collaborative partnership between Statistics Canada (STC) and Employment and Social Development Canada (ESDC). The release of the NOC 2021 will be the product of this 10-year cycle and will reflect changes in the economy and the nature of work. Input from the public, and particularly stakeholders has been a key part of the revision process.

The current NOC structure (NOC 2016) is categorized based on two major attributes of jobs, the "Broad Occupational Category" and the "Skill Level", as classification criteria. The former is defined as the type of work performed, with respect to the educational discipline or field of study for entry into an occupation and the industry of employment (e.g. health occupations or sales and service occupations). The "Skill Level" categorization is defined first by the amount and type of education and training usually required to enter and perform the duties of an occupation, but also considers experience, complexity and responsibilities. See Schedule A for details.

Revising the NOC

During consultation, it was suggested to add a new "Skill Level" to the current categorization, to clarify the distinction in formal training or education actually required among unit groups, especially in the current "Skill Level B", which has a wide range of formal training or educational requirements. The NOC 2016 "Skill Level B" includes all occupations usually requiring two to three years of post-secondary education at community college, institute of technology or CÉGEP or two to five years of apprenticeship training. In the NOC 2016, 211 occupations (42%) were classified under "Skill Level B", creating a disproportionately large group and thereby limiting the ability to analyze distinctions amongst a large percentage of occupations.

Another observation during the revision process was the use of the "Skill Level" categorization in the NOC as possibly being misleading because training and education, which are the main building blocks of the NOC's "Skill Level" categorization, are not considered as "skills" in the labour market. With regards to skills, many countries and organizations are currently developing their own skills taxonomy (which include concepts such as numeracy and literacy). Therefore, it was deemed appropriate for the NOC to move away from the "Skill Level" categorization.

The NOC 2021 revision will overhaul the "Skill Level" structure by introducing a new categorization representing the degree of Training, Education, Experience and Responsibilities (TEER) required for an occupation.

The new "TEER" categorization redefines the requirements of the occupation by reconsidering the type of education, training and experience required for entry, as well as the complexities and responsibilities typical of an occupation. In general, the greater the range and complexity of occupational tasks, the greater the amount of formal education and training, previous experience, on-the-job training, and in some instances responsibility, required to competently perform the set of tasks for that occupation.

Legislative and senior management occupations are classified in "TEER" 0 and defined as Management as they generally require and have a significant level of experience, knowledge and responsibilities related to resource planning and directing. Occupations classified under "TEER" 1 usually require university education or previous experience and expertise in subject matter knowledge from a related occupation found within TEER 2. Occupations usually requiring post-secondary education of two to three years, or apprenticeship training of at least two years, or occupations with supervisory or significant safety responsibilities are classified in "TEER" 2, and "TEER" 3 for those occupations requiring less than two years of post-secondary education or on-the-job training, training courses or specific work experience of more than six months. Occupations usually requiring a high-school diploma or no formal education are classified in "TEER" 4 or "TEER" 5. See Schedule B for the complete NOC 2021 restructure.

These changes significantly improve how the NOC classification takes into account the distinctions in formal training and educational requirements and better reflects skill and knowledge development occurring through on-the-job experience. At the same time, it increases the homogeneity of the distribution of unit groups within the classification, and addresses concerns about the "Skill Level" categorization and the distribution of unit groups among them.

The redesign of the NOC for 2021 moves away from the current NOC four "Skill Level" categories to an innovative six-grouping "TEER" categorization. This change is necessary for several reasons. First, the "Skill Level" terminology is often misleading for many stakeholders. This change will reduce confusion. Second, some NOC users artificially create or infer a low- and high-skill categorization. This redesign moves away from high/low skill categorization as the TEER more accurately captures differences in occupational requirements, which in turn will aid in the analysis of occupations.

The transition from the "Skill Level" to the "TEER" categorization makes the distribution of occupations across the "TEER categories" more balanced. The change in the distribution of unit groups is summarized in the tables below.

Distribution of NOC Unit Groups by Skill Level

Distribution of NOC Unit Groups by Skill Level

NOC 2016
Skill Level A	28%
Skill Level B	42%
Skill Level C	24%
Skill Level D	6%

Distribution of NOC Unit Groups by TEER

Distribution of NOC Unit Groups by TEER

NOC 2021
TEER Category 0	9%
TEER Category 1	19%
TEER Category 2	31%
TEER Category 3	14%
TEER Category 4	18%
TEER Category 5	9%

Note: The NOC 2021 final distribution may change when structure is finalized.

Impact on users

The structure and format of the current National Occupational Classification 2016 version are based on the four-tiered hierarchical arrangement of occupational groups with successive levels of disaggregation. It contains broad occupational categories, major, minor and unit groups.

The format of NOC 2021 will use a five-tiered hierarchical arrangement of occupational groups with successive levels of disaggregation and will contain broad, major, sub-major, minor and unit groupings. The structure of the National Occupational Classification 2021 is based on two key occupational categorizations: Occupational categories and TEER categories, which are identified in the first two digits of the NOC 2021 5-digit code. The 5-digit code will be structured as follows: XX.XXX. See Schedule B for details of the two important groupings.

It is important to note that the redesign of the NOC will have significant implications for several Statistics Canada (STC) Surveys, such as the Labour Force Survey (LFS), and ESDC programs such as the Temporary Foreign Worker Program and Employment Insurance program. This change may have significant impact on various programs throughout other federal departments, as well as provincial, territorial and municipal governments and many users of the NOC.

The NOC 2021 will be published in early 2021 and will become the departmental standard for data collection and dissemination for occupations at Statistics Canada. Implementation dates for the new classification version will vary based on when programs, entities, organizations or individuals decide to use it. For example, Immigration, Refugee and Citizenship Canada (IRCC), in conjunction with ESDC, is aiming to adopt the revised NOC structure in spring 2022 for the management of temporary and permanent resident programs. These dates will be confirmed on IRCC websites closer to the date of implementation.

As a normal practice, in advance of a full classification revision release, Statistics Canada will provide a spreadsheet of the actual structure of the classification, including the unit group numbers and corresponding titles. We will also provide a correspondence table between the NOC 2016 and the NOC 2021 unit groups and their corresponding titles. These products will be posted on our website by December 2020. This notice is being sent out now to inform all NOC users of the upcoming change which is currently being finalized. In early 2021, the full classification will be released, including the Leading Statements, Main Duties, Employment Requirements, Example Titles, Inclusions, Exclusions and Additional Information.

For additional questions, please contact the Statistics Canada NOC team at:
statcan.opmicquestionsmailbox-bgpvpcicourieldequestions.statcan@statcan.gc.ca

Schedule A – NOC 2016

NOC 2016

NOC 2016

The skill type category is…	when the first digit is…
Management occupations	0
Business, finance and administration occupations	1
Natural and applied sciences and related occupations	2
Health occupations	3
Occupations in education, law and social, community and government services	4
Occupations in art, culture, recreation and sport	5
Sales and service occupations	6
Trades, transport and equipment operators and related occupations	7
Natural resources, agriculture and related production occupations	8
Occupations in manufacturing and utilities	9

NOC 2016 skill level criteria - education/training and other criteria

NOC 2016 skill level criteria - education/training and other criteria

The Skill Level category is…	when the second digit is…
Skill Level A	0 or 1
Skill Level B	2 or 3
Skill Level C	4 or 5
Skill Level D	6 or 7

Skill Level A

• University degree (bachelor's, master's or doctorate)

Skill Level B

• Two to three years of post-secondary education at community college, institute of technology or CÉGEP
  or
• Two to five years of apprenticeship training
  or
• Three to four years of secondary school and more than two years of on-the-job training, occupation-specific training courses or specific work experience
• Occupations with supervisory responsibilities are also assigned to skill level B.
• Occupations with significant health and safety responsibilities (e.g., fire fighters, police officers and licensed practical nurses) are assigned to skill level B.

Skill Level C

• Completion of secondary school and some short-duration courses or training specific to the occupation
  or
• Some secondary school education, with up to two years of on-the-job training, training courses or specific work experience

Skill Level D

• Short work demonstration or on-the-job training
  or
• No formal educational requirements

Skill level is referenced in the code for all occupations with the exception of management occupations. For all non-management occupations, the second digit of the numerical code corresponds to skill level. Skill levels are identified as follows: level A – 0 or 1; level B – 2 or 3; level C – 4 or 5; and level D – 6 or 7.

Schedule B – NOC 2021

Schedule B – NOC 2021

Title of Hierarchy	Format	Digit	Represents:
Broad Category	X	First Digit – X	Occupational categorization
Major Group	XX	Second Digit xX	TEER categorization
Sub-major Group	XX.X	xx.X	Top level of the Sub-Major Group
Minor Group	XX.XX	xx.XX	Hierarchy within the Sub-Major Group
Unit Group	XX.XXX	xx.XXX	Hierarchy within the Minor Group

Note: The first digit identifies the Occupation, the second digit identifies the TEER. Therefore, the first 2 digits put together are identified as the Major Group. The next 3 digits identify their hierarchy within the groups.

Schedule B – NOC 2021

Broad Category - Occupation	when the first digit is…
Legislative and senior management occupations	0
Business, finance and administration occupations	1
Natural and applied sciences and related occupations	2
Health occupations	3
Occupations in education, law and social, community and government services	4
Occupations in art, culture, recreation and sport	5
Sales and service occupations	6
Trades, transport and equipment operators and related occupations	7
Natural resources, agriculture and related production occupations	8
Occupations in manufacturing and utilities	9

Schedule B – NOC 2021

The Training, Education, Experience and Responsibility (TEER)	when the second digit is…
Management - TEER	0
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).	1
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).	2
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).	3
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).	4
Short work demonstration and no formal educational requirements.	5