Retail Commodity Survey: CVs for Total Sales August 2022

Retail Commodity Survey: CVs for Total Sales July 2022
Table summary
This table displays the results of Retail Commodity Survey: CVs for Total Sales (July 2022). The information is grouped by NAPCS-CANADA (appearing as row headers), and Month (appearing as column headers).
NAPCS-CANADA Month
202205 202206 202207 202208
Total commodities, retail trade commissions and miscellaneous services 0.63 0.61 0.74 0.61
Retail Services (except commissions) [561]  0.63 0.61 0.73 0.60
Food at retail [56111]  0.56 0.52 1.84 0.81
Soft drinks and alcoholic beverages, at retail [56112]  0.59 0.61 0.71 0.58
Cannabis products, at retail [56113] 0.00 0.00 0.00 0.00
Clothing at retail [56121]  1.00 0.93 0.88 1.40
Footwear at retail [56122]  1.51 1.22 1.55 2.16
Jewellery and watches, luggage and briefcases, at retail [56123]  5.44 5.89 5.87 5.51
Home furniture, furnishings, housewares, appliances and electronics, at retail [56131]  1.31 1.05 1.02 0.95
Sporting and leisure products (except publications, audio and video recordings, and game software), at retail [56141]  1.60 1.93 1.84 1.84
Publications at retail [56142] 5.62 6.05 5.65 9.39
Audio and video recordings, and game software, at retail [56143] 0.31 1.17 1.00 0.34
Motor vehicles at retail [56151]  2.21 2.14 2.44 2.07
Recreational vehicles at retail [56152]  6.99 2.88 3.71 5.03
Motor vehicle parts, accessories and supplies, at retail [56153]  1.83 1.84 1.81 1.73
Automotive and household fuels, at retail [56161]  1.86 1.61 1.66 1.87
Home health products at retail [56171]  2.54 2.58 2.47 2.39
Infant care, personal and beauty products, at retail [56172]  1.97 2.25 2.03 2.20
Hardware, tools, renovation and lawn and garden products, at retail [56181]  1.60 2.41 2.06 2.08
Miscellaneous products at retail [56191]  3.12 2.89 2.41 2.45
Total retail trade commissions and miscellaneous services Footnote 1 1.84 1.88 1.96 1.75

Footnotes

Footnote 1

Comprises the following North American Product Classification System (NAPCS): 51411, 51412, 53112, 56211, 57111, 58111, 58121, 58122, 58131, 58141, 72332, 833111, 841, 85131 and 851511.

Return to footnote 1 referrer

Statistics Canada seeking perspectives on the use of linked administrative data

Deliberative public engagement research event objectives

Statistics Canada is conducting a deliberative public engagement research event on administrative data and data linkage in support of current and future statistical programs.

Statistics Canada is engaging with Canadians from diverse perspectives to seek feedback on the use of linked administrative data for social insights.

How to get involved

The series of deliberative discussions will be carried out in the fall of 2022 and recruitment for participation is now closed.  Individuals who wish to obtain more information on the consultation may contact: jenneke.lemoullec@statcan.gc.ca.

Statistics Canada is committed to respecting the privacy of all engagement participants. All personal information created, held or collected by the agency is protected by the Privacy Act. For more information on Statistics Canada's privacy policies, please consult the privacy notice.

Results

Summary results will be published online when available.

Date modified:

Canadian Statistics Advisory Council 2022 Annual Report - Trust, Governance and Data Flows in the National Statistical System

Release date: November 16, 2022

 PDF version (583.48 KB)

Message from the Canadian Statistics Advisory Council

A national statistical system is the cornerstone to providing Canadians with timely, regional and local data they need. Canadians need trusted and detailed data that reflect their day-to-day experiences to make personal and family decisions and run their businesses. Governments also need access to high-quality data to design and deliver effective public services.

Presently, organizations in both the public and private sectors are driving the use of digital information, as well as generating new data at unprecedented rates. There is now a proliferation of data held by governments, financial institutions, corporations, the research sector, private data analytics firms and data mining companies. Yet abundance of data does not automatically translate into ease of use and insights. Appropriate data governance and coordination are needed for developing the right information Canadians and decision makers need.

This is exactly what we tackle in this year's report. We examine the need for new types of partnerships and data coordination to support Canadians and our leaders as the country recovers from the pandemic and deals with socioeconomic and global environmental challenges.

This focus builds on our first two reports. In 2020, our report showed how the COVID-19 pandemic made evident the statistical challenges of not having timely, consistent and disaggregated data in areas such as health and on racialized Canadians and Indigenous peoples. In our second report, in 2021, we focused on principles for the development of a national statistical system to address critical data needs, including data stewardship considerations, new partnerships, and capacities for making greater use of Canada's wealth of existing and potential data resources. We believe these are essential for building the infrastructure needed for a vibrant economy and a healthy population, and for meeting the pressing problems the country faces today and in the years to come.

For Canada to succeed in an increasingly dynamic digital world, Statistics Canada's leadership role in the national statistical system is key. The agency's employees should be commended for building on opportunities presented by the rapid changes sparked by the COVID-19 pandemic. They helped accelerate Statistics Canada's modernization efforts and reinforced the agency's position as a leader of innovation both at home and internationally. They also worked to create new infrastructure for collaborating and coordinating information.

In some areas, new partnerships, innovative data sources and data sharing technologies have made a big difference to the detail and timeliness of key indicators provided by Statistics Canada. These changes include completing the transformation to a contactless census, with most Canadians now filling out their census questionnaire online. The agency also reflected changing consumer spending practices in its calculation of inflation, used satellite imagery as an innovative data source to better capture growth of crops and made Canada the first country to introduce non-binary gender on the census. The agency plays a leading and collaborative role internationally, creating and promoting cutting-edge statistical methods that recognize national interests.

Still, our work over the last three years shows that critical data gaps remain. In crucial sectors, the national statistical system is hampered by fragmentation, unused data and unmet data needs. New governance models are needed that drive innovative methods and data uses. These require broader partnerships to bring new perspectives. Furthermore, statistical legislation and policy practices must also be reviewed to re-evaluate the collection and use of critical data.

Through our work, we have observed that there are overly simplistic views on many issues that are fundamental to the statistical system. There is also a broad lack of data literacy. For example, there is no conflict between respect for the privacy of Canadians and the need for Canadians to contribute data to the national statistical system. Yet researchers and decision makers are concerned over the inability to access the data they need. Some people question why data are being collected, how they will be used and what measures exist to protect data privacy. Many feel there are inadequate legislative and regulatory measures to promote the innovative use of data and at the same time protect the privacy of their personal information and prevent the potential harmful use of individual data.

We are grateful to Statistics Canada, the Chief Statistician of Canada (who is an ex officio member of the Council) and his excellent team for responding to our requests for information with both written and oral presentations. We would like to offer our very particular thanks to Romy Ochmann St-Jean, Sam Ndayishimye, Kacie Ha and Gaëlle Miollan of the Canadian Statistics Advisory Council Secretariat for their advice and assistance. We are also grateful for the work of Gail Mc Donald, Gurmeet Ahluwalia and Dr. Michael C. Wolfson and their insights as members of the Council.

For us, the best way to provide Canadians with these data is to ensure that the national statistical system has strong statistical leadership. This should be built upon mutually beneficial collaboration and partnerships across all levels of government and sectors. There is too much at stake for Canadians and communities not to have access to the statistical information they need to make decisions for today and tomorrow.

Signed:
The Canadian Statistics Advisory Council

Dr. Howard Ramos, chairperson
Annette Hester
Dr. Céline Le Bourdais
David Chaundy
Jan Kestle

Executive summary

Information and data are the foundations of a modern and diverse digital economy. They are also the foundations of national and official statistics. High-quality statistical information is among Canada's most valuable resources. A robust national statistical system is driven by innovation that crosses all sectors and communities. Canadians require disaggregated, timely, regional and local data to make personal and family decisions and run their businesses. Governments need these data to make informed decisions in times of crisis and every day as they provide public services.

The fast pace of social and economic change is affecting the kinds of data and analyses Canadians need. There has been a dramatic shift in how Canadians collect and receive information, with a proliferation of digitized data banks, sensor data and social media. New tools are being used to produce, collect, map, process, transform and visualize information.

However, data gaps remain in key areas that touch everyone, such as the environment and health. For example, there is a need to track and better understand the more frequent and devastating environmental occurrences to inform climate change policy and adaptation. As well, a recent expert advisory report to the Public Health Agency of Canada, Toward a world-class health data systemFootnote 1 indicated that "failure to collaborate across Canada to build a learning health system risks continued escalation of health care costs, underperformance of health services and poor health outcomes including: avoidable illness and death, low levels of innovation, perpetuation of health inequities, and ineffective responses to future public health threats."

It is in the interest of Canadians, businesses and governments to ensure a national statistical system that promotes the sharing and integration of data across jurisdictions and sectors. For Canada to succeed in a dynamic digital economy, public and private organizations must collaborate to produce coherent and trusted statistical information. The true power of data comes with shared standards and coordination. There should be greater investment by the federal government and other sectors in implementing and maintaining state-of-the-art software and communications technologies to facilitate this data sharing. This would enable timely collection of important data to build a truly national data infrastructure.

As a country, Canada also needs to move past old debates around data and privacy that dominate ongoing discussions of these issues. The interpretation of statistical legislation needs to reflect a modern economy. For example, it is important to be able to responsibly obtain data not currently available in areas that are considered critical, such as in the energy, natural resources and environmental sectors.

This shift includes moving the thinking from simply the collection of data to also discussing the access and use of data. There needs to be a more extensive and informed conversation about the responsible, innovative use of data in a digital economy and the privacy of information. This includes a balance between individual rights and collective needs.

Recommendations

Recommendation 1:
Maintain the authority and responsibilities of Statistics Canada

There is no conflict between respect for the privacy of Canadians and the need for Canadians to contribute data to the national statistical system. It is in the interest of Canadians, businesses and governments to ensure a national statistical system that protects the privacy of Canadians' data and at the same time promotes the sharing and integration of data across jurisdictions and sectors.

The Minister of Innovation, Science and Industry should ensure that the authority and responsibilities of Statistics Canada are not diminished or compromised by privacy or other legislation related to data and digital infrastructure.

Recommendation 2:
Strengthen data stewardship within the national statistical system

Statistics Canada has a critical role to play in ensuring that Canada has the data it needs to successfully tackle social, economic and environmental challenges in a digital world. There should be no ambiguity around its responsibilities in national data standards and data flows.

 
  • 2.1 The Minister of Innovation, Science and Industry should
    1. ensure that the authority and responsibilities of Statistics Canada as data steward within the national statistical system are strengthened, both in legislation and governance
    2. ensure that new federal programs are mandated to include an assessment of data needs and have the resources to support the development and integration of data flows.
  • 2.2 The Chief Statistician of Canada should
    1. maintain and build on the momentum of the agency's efforts in addressing data gaps through new partnerships, modernization and innovation
    2. better navigate the complex landscape of data acquisitions from within the private sector and other sectors
    3. continue to improve access to and use of data obtained by Statistics Canada.

Recommendation 3:
Strengthen data sharing across jurisdictions

National data strategies should develop multi-jurisdictional approaches to addressing data needs in Canada, including provincial, territorial and regional data flows. When data are shared across jurisdictions, the benefits to health, social, economic and environmental outcomes increase dramatically.

 
  • The Minister of Innovation, Science and Industry should
    1. ensure there is the legal, governance and resource support required for coordinating and sharing data across jurisdictions according to data standards
    2. ensure the federal government makes fiscal transfers contingent on data flows that can be integrated into the national statistical system.

Trust must be at the forefront of the national statistical system

The national statistical system is based on a foundation of trust. Canadians value the protection of the personal data they share. They also value Canadian innovation in supporting a modern digital economy.

Canadians entrust their data to Statistics Canada, which has a long-standing track record of providing high-quality and timely statistics. The agency's statistical and technical expertise in creating nationally comparable data is highly regarded within Canada and internationally. Data protection is at the forefront of every activity the agency does, from the collection of individual data to access to detailed local results.

Canadians trust Statistics Canada more than other institutions. Almost 90% of Canadians trust Statistics Canada, according to an EKOS public opinion survey conducted in 2018Footnote 2 This is a much higher level of trust than that in other government institutions, banks and financial institutions, private market research or polling companies, and the media. As well, 98% of Canadians complete the census every five years. Also, rather than answer detailed financial questions on the census, the majority of Canadians allow Statistics Canada to access their income tax records.

At the same time, many studies, including the 2022 Edelman Trust Barometer: Trust in CanadaFootnote 3Charity ReportFootnote 4 and Proof Strategies CanTrust IndexFootnote 5 have shown a downward trend in trust in governments, businesses and media that predates the pandemic. This trend is driven by Canadians who feel anxiety as they deal with a rapidly shifting economy and a changing society, now compounded by the effects of the pandemic.

Yet this is precisely the time when Canadians and their governments require timely, independent, high-quality statistics. It has never been more important for Statistics Canada and the national statistical system to deliver on this service. Outreach by Statistics Canada to Canadians is important as they grapple with issues such as privacy and data literacy. The new Trust Centre web portal and the agency's Necessity and Proportionality Framework are good examples of how Statistics Canada is taking action to become more transparent about how data are collected and used.

Privacy legislation must recognize and integrate Statistics Canada's authorities

Laws and governance around statistics, data infrastructure and data protection need to be clear and unambiguous. They especially need to clearly define the authorities of governments and the rights of Canadians.

For example, in response to the COVID-19 pandemic, the Public Health Agency of Canada in 2020 began using smartphone mobility dataFootnote 6 to help develop public policy and determine where to allocate much-needed resources. This action met the needs and expectations of Canadians who wanted more granular and timely data on the trajectory of the pandemic. Although the government used properly de-identified data to assess mobility patterns, privacy advocates argued that the current regulatory framework and federal privacy laws do not adequately address the use of data, particularly de-identified or aggregated data. Such arguments favour individual concerns over the collective needs and expectations of society. These concerns, however, can be mitigated through legislation and policy practice, as well as data literacy.

Canada and many other countries are reviewing their data protection laws, given the dramatic increase in the prevalence and use of personal information from administrative data. This review includes the consideration of new technologies, such as artificial intelligence, machine learning, and mobile and tracking data. Internationally, there are growing concerns about the data holdings collected by multinational companies and the information they scrape from the Internet.Canada needs to amend its legislation by the end of 2022 to comply with European Union legislation that affects, among other things, global trade.

In the spring of 2022, the Canadian government introduced Bill C-27, the Digital Charter Implementation ActFootnote 7. The proposed legislation will ensure the continued safety and trust of Canadians in the digital environment in terms of private sector use of personal information and use of technology. It revises the Personal Information Protection and Electronic Documents Act (PIPEDA)Footnote 8, which set the ground rules for how private sector organizations collect, use and disclose personal information. The new legislation reflects the principles of the Digital CharterFootnote 9 launched in 2019, a blueprint for digital transformation in Canada.

The Canadian Statistics Advisory Council supports the planned revisions to PIPEDA. The new legislation is very welcome as the federal government enables responsible data innovation in a data-driven, digital and global economy.

At the same time, the Council has concerns on what governance there will be for the interpretation and application of the legislation. Without the proper expertise and authorities, there is potential for ambiguity. Caution is needed to ensure that privacy concerns do not, through law or policy interpretation, compromise the ability of government, the private sector and the research sector to access and use critical data in responsible, innovative ways.

Statistics Canada has the legal authority to collect federal, provincial and territorial data under the Statistics Act. The act also gives the agency the authority to collect data from the private sector and individuals. Most provincial and territorial jurisdictions include provisions in their data protection laws to permit data sharing with Statistics Canada for statistical purposes. The confidentiality of this information is already protected under the Statistics Act.

It is disconcerting that excessive powers of oversight and enforcement on technical statistical matters, such as those related to the use of de-identified data, would be attributed to the Privacy Commissioner in the proposed legislation.

Technical statistical matters should be assessed and governed by statistical experts in conjunction with privacy officials. The Council continues to advocate that federal, provincial and territorial data protection laws and policies recognize the imperative of data sharing for statistical purposes. There should be no legislative ambiguities with regard to Statistics Canada's authority to obtain these data under the Statistics Act.

The Council's recommendation this year reinforces this point. Federal agencies should work with Statistics Canada to ensure revisions to privacy legislation recognize and integrate these authorities for statistical purposes. All sectors should understand that the new legislation does not impede the coordination and sharing of data with Statistics Canada. Rather, new statistical methods and technologies have opened up possibilities to continue to protect the privacy of Canadians' personal information while bringing together more granular social, economic and environmental data that are important for tackling the issues Canadians face.

Statistical governance and data flows must be strengthened

Data gaps in areas such as health, the economy and the environment touch everyone, and Canadians are continuing to pay the price for a lack of coordinated and accessible data. For example, there is a need to track and better understand the more frequent and devastating environmental events to inform climate change policy and adaptation. These include floods, forest fires and droughts affecting Canadians and the country's natural resources. There also must be a better understanding of how business data critical for economic indicators can be provided without affecting a business's competitiveness. There is a need to understand and address barriers and inequities faced by racialized groups and Indigenous peoples, across Canada and at the local level. Canadians are also adopting new social, consumer and labour practices as a result of societal changes that have been evolving over decades. Accelerated and amplified by the pandemic, many of these practices will remain in some form.

Strengthening the national statistical system requires long-term and sustained leadership and commitment from the public, private and non-governmental sectors across Canada. A truly national statistical system is one where all sectors play a role. At the same time, stronger authorities and governance are necessary to ensure the coordination of data across sectors and to promote data flows in areas where barriers have hindered progress for many years.

Central to improving data flows within the Canadian statistical system are better relationships and partnerships across jurisdictions and with Indigenous peoples, the academic sector, non-governmental organizations (NGOs) and the private sector. When founded on trust, respect and meaningful engagement, these partnerships can lead to mutually beneficial opportunities, creating the data Canadians need and providing access to these data.

Movement toward a more comprehensive and inclusive national statistical system would benefit from broader consultations and engagement with stakeholders and communities. These include outreach to experts and voices that may at times be non-conventional.

Statistics Canada's legal mandate includes promoting and facilitating the interoperability of data flows so that data collected and shared from a range of public and private sources can better contribute to the national data system. While the agency's legal mandate and stewardship have served Canadians well, they need to be strengthened to deal with new and long-standing barriers to data development and data flows.

The agency should be recognized as a prime national data steward to ensure that Canada has the data it needs. There should be no ambiguity around its responsibilities and authorities. The Council's 2021 reportFootnote 10 presented principles of data stewardship that outline the relationships Statistics Canada should have with other government jurisdictions, Indigenous organizations and the private sector. The key duties of such stewardship are around coordinating data, setting shared standards and promoting the exchange of data.

Federal statistical system

In 2019, the federal government launched the Digital Charter, a blueprint for digital transformation in Canada. This is too important to be left to informal ad hoc initiatives. In Budget 2021Footnote 11, the government reinforced its commitment to a whole-of-government approach to help protect people's personal data and encourage innovation in the digital marketplace. Defining and prioritizing data needs should thus be an integral part of federal program planning. Without a holistic approach, opportunities and investments are lost. Too many government programs lack an upfront assessment of statistical measures required to successfully develop, monitor and assess the relevance and effectiveness of programs. They also often fail to consider the resources needed to fulfill such assessments. Opportunities are missed for collaborating with other programs to develop data strategies that would not only serve common needs, but result in more comprehensive and enriched data.

The stewardship role of Statistics Canada must be clearly articulated and recognized in the governance of federal program planning to ensure the right statistics are identified and developed. With federal programs representing billions of dollars in investments, there is a significant financial cost to keeping the long-standing culture of narrow and siloed departmental data governance. This situation also adds a burden for Canadians, who are unnecessarily asked to provide the same information in multiple surveys and to different parts of the federal government, not to mention other jurisdictions.

The 2021 federal budget tasked Statistics Canada with creating a Disaggregated Data Action Plan to fill data and knowledge gaps. As Statistics Canada continues to consider new approaches to enable more detailed data on diverse population groups, the Disaggregated Data Action Plan has allowed the agency to improve and expand data collection in its major surveys. For example, this has resulted in the release of labour market information for visible minority groups. As well, Statistics Canada will now be able to release timely data on business conditions in Canada for businesses that are majority-owned by women, by visible minority sub-populations, by Indigenous peoples, by persons with a disability, and by immigrants to Canada. In addition, the agency has been a leader in linking data including administrative data to make up for shortfalls in other sources of information. An integrated approach through innovation and use of multiple and modern methodologies generally means more disaggregated data can be produced.

Provincial, territorial and regional data flows

As a national data steward, Statistics Canada does not have to, and should not, collect and control all the data in the country. Most data in Canada are collected by government departments at all levels of jurisdiction and by the private sector. Collected primarily to meet the administrative and operational needs of organizations, these data can be invaluable to the national statistical system if they are collected in a coordinated manner with common data standards.

When data are shared across jurisdictions, the benefits to health, social, economic and environmental outcomes increase dramatically. For example, to meet the demands for new types of data on biodiversity, clean technology, sustainable agriculture and reduction in plastic waste, there needs to be more sharing and integration of energy and environmental data from provincial and territorial governments, environmental NGOs, academic researchers, and the private sector.

National data strategies should present multi-jurisdictional approaches to addressing data needs in Canada, including provincial, territorial and regional data flows. There should be greater investment by the federal government and other sectors in implementing and maintaining state-of-the-art software and communications technologies to enable and coordinate the timely collection of important data across jurisdictions to build a truly national data infrastructure.

Integrating data at provincial and territorial levels has added complexity when jurisdictions become siloed, and legislation and policies create barriers to data sharing. It has been next to impossible to develop national comparative data for some critical areas.

For example, health is a complex and intricate sector, with large numbers of subsectors that interconnect with many social, economic and environmental disciplines. The governance structures for health data are often fragmented, with limited authority to coordinate data nationally. There is no central governance structure in Canada to oversee pan-Canadian health statistics. The recent expert advisory report to the Public Health Agency of Canada, Toward a world-class health data systemFootnote 12, and this agency's Pan-Canadian Health Data StrategyFootnote 13 represent positive efforts to address these issues.

There is also no central governance structure in Canada to provide official statistics in other domains such as the environment, natural resources and energy. Given the relevance of environmental challenges for decades to come, data requirements and funding for these areas should be based on a holistic approach involving all levels of government and private sector companies. As Canada moves to tackle climate change and address the United Nations' Sustainable Development Goals, it needs to transition from collecting information on resources alone to creating new models and measures that transcend jurisdictions to look at energy, the environment, the economy and social demographic factors multidimensionally. To be effective at tackling the greatest problem that countries will face this century, coordination and partnerships will be key.

More substantive debates are required about holding provinces and territories accountable to Canadians in terms of sharing data and statistical information for the billions of dollars transferred annually to provide health services. As the Council has recommended in previous reports, there should be an obligation under the transfer agreements for provinces and territories to share individual-level data with Statistics Canada for statistical purposes.

Indigenous-led data strategies

Indigenous-led data strategies are integral to the national data system. First Nations, Inuit and Métis communities are developing distinctions-based approaches to asserting their unique jurisdiction, ownership and control over their data. Indigenous-led data development and capacity investments are essential at the community, regional and national levels to support these efforts. Statistics Canada can play an important role in enhancing opportunities for communities and organizations to contribute to nationwide data development.

Relationships with governments are important in shaping trust and building partnerships. Over the coming years, as First Nations, Inuit and Métis implement their data strategies, there are opportunities for new collaborative frameworks to foster meaningful and long-term partnerships, enable mutual learning across jurisdictions, advance innovation, and guide transformative initiatives toward a more inclusive and stronger national statistical system. Distinctions-based relationships ensure that the unique rights, interests and circumstances of First Nations , Inuit and Métis over their data are acknowledged, affirmed and acted upon.

For this approach to be successful, First Nations, Inuit and Métis must be fully part of the governance structures of the national statistical system. In particular, Indigenous peoples, through their representative data organizations, should participate at appropriate federal data committees and tables.

The First Nations Information Governance CentreFootnote 14 and its regional partners are playing a leadership role in developing and implementing the First Nations Governance Data StrategyFootnote 15. This strategy reflects priorities for establishing a First Nations-led network of fully functioning, interconnected data and statistical service centres, or Regional Information Governance Centres. This process includes developing all the capacities needed to best meet the data and statistical needs of First Nations communities, their governments, and their political and service delivery organizations.

The communities of Inuit NunangatFootnote 16 face particular opportunities and challenges in the rapidly changing Canadian Arctic. Inuit Tapiriit KanatamiFootnote 17 has developed the National Inuit Strategy on ResearchFootnote 18 to improve the way Inuit Nunangat research is governed, resourced, conducted and shared. ArcticNet'sFootnote 19 Inuit-led research program involves universities, companies, governments, non-profit organizations and Indigenous organizations across Canada and worldwide to advance collective knowledge of the Arctic through research and knowledge sharing efforts.

The Métis National CouncilFootnote 20 has created web information portals and data tools to share information on Métis Nation governance in areas such as the environment, economic development and Métis healing.

Today, much Indigenous-led research and efforts to leverage their own data are hampered by how data on Indigenous peoples can be accessed and used once they are collected. The national statistical system would benefit from Statistics Canada working with Indigenous organizations, federal agencies and other jurisdictions to resolve long -standing legal and policy issues around data sovereignty.

Private sector

There is a wealth of private sector data in this country that are not integrated within the national statistical system. The need for timely sharing and integrated analysis for the public good has never been more critical. When built upon shared standards and definitions, these data can fill critical gaps and help inform some of the more complex social, economic and environmental issues Canadians face.

Many leading-edge private sector organizations are driving the use of digital information to do just that. As Canadians show an appreciation for the value of good data, there is an opportunity for increased collaboration with private sector partners. Statistics Canada has a role to play in helping coordinate data standards, promote data flows and ensure data protection.

At the forefront of this issue is building and maintaining a strong position of trust with Canadians in an environment of heightened sensitivity for the protection of personal data. The ability of Statistics Canada to partner with the private sector can be hampered by ambiguity or misperceptions of existing legislation and policy practices. There needs to be more informed public dialogue in Canada about the alignment of data in a digital economy that is key to effective decision making and the privacy of information.

Canada's future success is contingent on a strong national statistical system

The value of the wealth of data in Canada is strongly correlated with cutting -edge innovations in how they are collected and used. Increasingly, detailed microdata are required by researchers and policy makers to better understand and address multidimensional issues. Informative statistics are founded on relevant, high-quality data, accessible from both established and innovative sources. Machine sensors, mobile phone data, banking data, administrative records and the Internet are at the cutting edge of data collection. The future of statistics is tied to the use of these new forms of data and measures that reflect the needs and concerns of the 21st century.

To this end, Statistics Canada's effort to modernize with investments in data science and cloud computing has been key. Infrastructure that promotes collaboration and coordination is essential. The agency has been a leader internationally in developing satellite data to help fill the deficiencies of surveys and censuses, as well as moving to new means of accessing and sharing information. Data are more accessible compared with having to visit the older brick-and-mortar data centres. The agency is also a leader in developing statistical concepts and data standards, such as new sociodemographic measures on gender and ethnocultural diversity.

Canada's future success is contingent on a strong national statistical system. It will be important to build on the momentum of new partnerships and modernization. At the same time, statistical governance and data flows must be strengthened to overcome long-standing data gaps in the critical areas of health, the economy and the environment. The roles and responsibilities around data coordination and integration must be unambiguous.

Definitions

Administrative data are holdings of individual records collected by government departments and other organizations for the purpose of administering benefits, services and taxes. Under provisions of the Statistics Act, administrative data can be shared with Statistics Canada for statistical purposes.

Data stewardship, in support of the national statistical system, is the coordination and facilitation of nationwide data to inform Canadians and the country's public and private decision makers. It ensures these data are of high quality, easily accessible and used in a consistent manner. It includes data collected and managed by federal, provincial, territorial, municipal and Indigenous jurisdictions, as well as by the private sector.

Distinctions-based Indigenous led processes for First Nations, Inuit and Métis, both in and outside their communities, acknowledge the unique rights and jurisdiction of each group to maintain ownership and control over data that relate to its identity, people, language, history, culture, communities, and nations, both historical and contemporary. Each will establish laws and regulations to govern its data and determine how they will be managed, accessed and shared with other governments, organizations or individuals. Each is uniqueand distinct.

Equity-deserving groups are designated groups under the Employment Equity Act for which the government is required to strive to meet representation levels based on estimated workforce availability. They include women, Indigenous peoples, persons with disabilities and members of visible minorities. The term also includesother groups that are disadvantaged, such as members of the 2SLGBTQIA+ community, who are not recognized in the act but are increasingly considered in government policies.

Indigenous as a term in this reportis understood at all times to mean First Nations, Inuit and Métis, living both in and outside their communities. Indigenous organizations, as referenced in this document, include the Assembly of First Nations, the Congress of Aboriginal Peoples, the First Nations Information Governance Centre, Inuit Tapiriit Kanatami, the Métis National Council and the Native Women's Association of Canada.

Integrating data involves linking records from different data sources on the same entity (i.e., a person or business). Microdata linkage is an internationally recognized statistical method that maximizes the use of existing information by linking different files and variables to create new information that benefits Canadians. Integrated microdata files should generally be created independently for research activities, and only on an as-needed basis. Linkage, storage and disposal protocols ensure the confidentiality of personal information.

Interoperability is the ability of different systems or products to connect and communicate in a coordinated way.

Microdata are individual records containing information collected from the census, surveys, administrative data and other sources. They may represent an individual, a household, a business or an organization. The confidentiality of identifiable information about individuals is protected under the Statistics Act.

Necessity and proportionality refer to principles applied to the collection of information. Statistics Canada considers needs for data to ensure the well-being of the country (necessity), and it also tailors the volume and detail of the data collected to meet these needs (proportionality).

A non-governmental organization (NGO) is a non-profit organization that operates independently of any government, typically one whose purpose is to address a humanitarian, social or political issue.

Racialized is a term increasingly used in place of "visible minority," a term that has been criticized in Canada and internationally, including by the United Nations. Racialized refers to people or groups who are categorized or discriminated against because of their racial background or appearance.

Statistical information is the added value to statistics resulting from quantitative interpretation, modelling and analysis. It can take many forms, including charts, interactive visualizations and analytical articles.

Canadian Association of University Business Officers (CAUBO)

Financial Information of Universities – 2021/2022

Canadian Centre for Education Statistics

This information is collected under the authority of the Statistics Act, Revised Statutes of Canada, 1985, Chapter S-19.

Although your participation in this survey is voluntary, your cooperation is important so that the information collected will be as accurate and complete as possible.

Purpose of the survey

This survey collects financial information (income and expenditures) on all universities and degree-granting colleges in Canada. Your information may also be used by Statistics Canada for other statistical and research purposes.

Confidentiality

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

Fax or e-mail transmission disclosure

Statistics Canada advises you that there could be risk of disclosure during the transmission of information by facsimile or e-mail. However, upon receipt, Statistics Canada will provide the guaranteed level of protection afforded all information collected under the authority of the Statistics Act.

Record linkages

To enhance the data from this survey, Statistics Canada may combine it with information from other surveys or from administrative sources.

General information

  • Name of University (or College)
  • Address of preparer
    • Street
    • City
    • Province
    • Postal Code
  • Fiscal year ending: Day Month Year
  • Name and title of preparer
  • Telephone
    • Area code
    • Number
    • Local
  • Fax
    • Area code
    • Number
  • E-mail address
  • Name of Senior Administrative Officer (if different from above)

Instructions

  1. Please read carefully the accompanying Guidelines.
  2. All amounts should be expressed in thousands of dollars ($'000).
  3. In the "Observations and Comments" section, please explain financial data that may not be comparable with the prior year.
  4. Please do not fill in shaded areas. All non-shaded cells should be completed.
    A nil entry should be indicated with a zero.

Reserved for Statistics Canada

  • Full-time equivalent
  • Report Status
  • Institution Code: nceYYIII
  • Comments
Table 1
Income by fund
Table summary
This is an empty data table used by respondents to provide data to Statistics Canada. This table contains no data.
Types of income Funds
General operating Special purpose and trust Sponsored research Ancillary Capital Endowment Total funds
Entities consolidated Entities not consolidated Sub-total
(thousands of dollars)
Government departments and agencies - grants and contracts  
Federal  
1. Social Sciences and Humanities Research Council                  
2. Health Canada                  
3. Natural Sciences and Engineering Research Council                  
4. Canadian Institutes of Health Research (CIHR)                  
5. Canada Foundation for Innovation (CFI)                  
6. Canada Research Chairs                  
7. Other federal (see Table 6)                  
Other  
8. Provincial (see Table 7)                  
9. Municipal                  
10. Other provinces                  
11. Foreign                  
Tuition and other fees  
12. Credit course tuition                  
13. Non-credit tuition                  
14. Other fees                  
Donations, including bequests  
15. Individuals                  
16. Business enterprises                  
17. Not-for-profit organizations                  
Non-government grants and contracts  
18. Individuals                  
19. Business enterprises                  
20. Not-for-profit organizations                  
Investment  
21. Endowment                  
22. Other investment                  
Other  
23. Sale of services and products                  
24. Miscellaneous                  
25. TotalNote 1                  

  Observations and comments

  • Description (Fund and type of income)
  • Comments
Table 2
Expenditures by fund
Table summary
This is an empty data table used by respondents to provide data to Statistics Canada. This table contains no data.
Types of expenditures Funds
General operating Special purpose and trust Sponsored research Ancillary Capital Endowment Total funds
Entities consolidated Entities not consolidated Sub-total
(thousands of dollars)
Academic salaries  
1. Academic ranks                  
2. Other instruction and research                  
3. Other salaries and wages                  
4. Benefits                  
5. Travel                  
6. Library acquisitions                  
7. Printing and duplicating                  
8. Materials and supplies                  
9. Communications                  
10. Other operational expenditures                  
11. Utilities                  
12. Renovations and alterations                  
13. Scholarships, bursaries and prizes                  
14. Externally contracted services                  
15. Professional fees                  
16. Cost of goods sold                  
17. Interest                  
18. Furniture and equipment purchase                  
19. Equipment rental and maintenance                  
20. Internal sales and cost recoveriesNote 1                  
21. Sub-total                  
22. Buildings, land and land improvements                  
23. Lump sum payments                  
24. TotalNote 2                  

Observations and comments

  • Description (Fund and type of expenditure)
  • Comments
Table 3
Statement of changes in net assets by fund
Table summary
This is an empty data table used by respondents to provide data to Statistics Canada. This table contains no data.
Objects Funds
General operating Special purpose and trust Sponsored research Ancillary Capital Endowment Total funds
Entities consolidated Entities not consolidated Sub-total
(thousands of dollars)
1. Net asset balances, beginning of year                  
2. Income (Table 1, line Total)                  
3. Expenditures (Table 2, line Total)                  
4. Prior year adjustments                  
5. Interfund transfersNote 1                  
6. Add: borrowings                  
7. Deduct: principal portion of debt repayments                  
8. Interfund reallocationsNote 1                  
9. Add: capital expenditures                  
10. Deduct: amortization                  
11. Add or deduct: deferred income                  
12. Add or deduct: pension costs and vacation pay accrual                  
13. Add or deduct: future cost of employee benefits                  
14. Add or deduct: related or affilitated entities                  
15. Add or deduct: other (provide details in space below)                  
16. Net asset balances, end of yearNote 2                  
Net asset balances are comprised of:                  
17. Unrestricted net assets                  
18. Investment in capital assets                  
19. Internally restricted net assets                  
20. Externally restricted net assets                  
21. Net asset balances, end of yearNote 2                  

Observations and comments

  • Description (Fund and object)
  • Comments
Table 4
General operating expenditures by function
Table summary
This is an empty data table used by respondents to provide data to Statistics Canada. This table contains no data.
Types of expenditures Functions
Instruction and non-sponsored research Non-credit instruction Library Computing and communications Administration and academic support Student services Physical plant External Relations Total functionsNote 1
(thousands of dollars)
Academic salaries  
1. Academic ranks                  
2. Other instruction and research                  
3. Other salaries and wages                  
4. Benefits                  
5. Travel                  
6. Library acquisitions                  
7. Printing and duplicating                  
8. Materials and supplies                  
9. Communications                  
10. Other operational expenditures                  
11. Utilities                  
12. Renovations and alterations                  
13. Scholarships, bursaries and prizes                  
14. Externally contracted services                  
15. Professional fees                  
16. Cost of goods sold                  
17. Interest                  
18. Furniture and equipment purchase                  
19. Equipment rental and maintenance                  
20. Internal sales and cost recoveries                  
21. Sub-total                  
22. Buildings, land and land improvements                  
23. Lump sum payments                  
24. Total                  

Observations and comments

  • Description (Function and type of expenditure)
  • Comments

Extracting Public Value from Administrative Data: A method to enhance analysis with linked data

By: Sarry Zheng and Howard Swerdfeger, Canada School of Public Service

The daily lives of Canadians are increasingly shaped by data-driven technologies and services. By using these technologies and services, the Government of Canada can access data from multiple sources to better serve the needs of citizens and inform decision-making.

One of the places to enhance analysis is Statistics Canada's Linkable File Environment (LFE), which helps unlock insights from administrative data to information on businesses and individuals across Canada. It ensures all confidentiality and disclosure rules are respected before releasing aggregated and vetted data. This creates an opportunity to access more accurate information and conduct comprehensive analyses. It also reduces the survey and reporting burden on departments and private industries.

What is linked data?

Linked data is the process in which records from different data sources are joined together into a single file using identifiers, such as names, date of birth, addresses, and other characteristics. It is also known as record linkage, data matching, and entity resolution, to name a few. The initial idea of linked data goes back to the 1950s. This technique is used in a wide range of fields such as data warehousing, business intelligence, and medical research.

Types of Linkage

There are two types of linkage – exact matching and statistical matching.

  1. Statistical matching creates a file to reflect the underlying population distribution. Records that are combined do not necessarily correspond to the same entity, such as a person or a business. It is assumed that the relationship of the variables in the population will be like the relationship on the file. This method is commonly used in market research.
  2. Exact matching links information about a particular record in one file to information in another file to create a single file with the correct information for each record. They can be divided into two subtypes – deterministic record linkage and probabilistic record linkage.Footnote 1
    • Deterministic record linkage – link records based on common identifiers between data sources
    • Probabilistic record linkage – link records where not all columns from the records are identical, based on a probability that the records match.

Probabilistic Record Linkage

When a dataset doesn't contain a unique identifier, is incomplete, or contains errors, probabilistic record linkage is a method that can be used to link data files and build a set of potential pairs. As in Figure 1, we can see that the first records are identical while the second and third records are a match, but not identical. The goal of any probabilistic record linking algorithm is to replicate a human's ability to see that these entities are the same with high confidence.

Figure 1: Sample datasets to be joined for probabilistic matching
Description - Figure 1: Sample datasets to be joined for probabilistic matching
Sample dataset 1
Company Name Address City Prov Postal Code Licence # Product Count
ABC Inc. 1072 Booth Street Saskatoon SK S5P 1E4 1111 50
XYZ Ltd. 118 Hammer Way Richmond BC V7A 5E5 1112 3
613 Canada Inc. 210 Glasgow Street Ottawa ON K1A 0E4 1113 500

Like to Like match, Threshold 97%

Sample dataset 2
Comp_nm Addr City Prov PC
ABC Inc. 1072 Booth Street Saskatoon SK S5P 1E4
XYZ Limited 118 Hammer Way Richmond BC V7A 5E5
613 Canada Incorporated 10200 - 210 Glassgow Street Ottawa ON K1A 0E4

Standard Practices

One of the tools Statistics Canada uses is SAS software called G-Link to perform probabilistic record linkages. G-Link represents a direct implementation of the Fellegi-Sunter record linkage algorithm, packaged in a Windows-based application.

As computational power continues to grow, allowing larger datasets to be linked in a shorter period and accessible on desktop computers, the development of new theoretical models and refinements of existing methodologies and software are becoming more prevalent. For instance, the record linkage toolkit in Python, and reclin in R are two easy-to-use examples that integrate well with the Fellegi-Sunter method of record linkage using open-source software.

Fellegi-Sunter

Since its publication, Fellegi-Sunter (1969)Footnote 2 has become the de facto approach for probabilistic record linkage. This model estimates match weights for each individual column and combines these match weights into an overall match probability. By assuming variables must be independent given the match status, it can be combined with Bayes Theorem and quantified using two key parameters for each column – the m and u probabilities, where:

  • m is the probability that a given column does not match but the records are the same.
  • u is the probability that a given column is the same, but the records are not.

Bayes Theorem is

PR|D=PD|R*PRPD

Where:

  • PR is the probability of a record match
  • PD is the probability of some data element matching

Expanding the denominator,

PR|D=PD|R*PRPD|R*PD+PD|R¯*PR¯

Where:

  • PR¯ is the probability that two records don't match or 1-PR

Since we have multiple columns or multiple lines of evidence, one could use mi, and ui for the m and u probabilities of the ith column.

PR|D=i=1Ncolmi*PRi=1Ncolmi*PR+i=1Ncolui*1-PR

Dr. Yvan P. Fellegi

Dr. Yvan P. Fellegi served as Statistics Canada's Chief Statistician from 1985 to 2008. In this role, he introduced new methods for collecting and compiling national statistics. In 1992, Fellegi became a member of the Order of Canada and upon his retirement in June 2008, the Canadian government appointed him Chief Statistician Emeritus.

String comparisons

Fellegi-Sunter has at least one disadvantage that is typically fixed in practical applications. In practice, for many columns the m and u probabilities are often not based on the probability that two columns are identical, but rather some appropriate distance function is used to measure the similarity between two columns and then calculate the threshold. The m and u probabilities would then be based on these thresholds.

For strings, several common distance functions exist - each one may be useful for the combination of data and expected differences (misspellings) in your dataset. Some of these are briefly summarized below:

Sample dataset 3
Distance Functions Company Name Comp_nm
Jaro-Winkler homers odyssey Incorporated homers odyssey Incorporation
Longest Common Substring Rumpelstiltskin Incorporated The Rumpelstiltskin Incorporation
Levenshtein distance Quasimodo and Esmeralda Inc. Quazimodo and Ezmeralda Inc.
Cosine William "Bill" S. Preston and Ted "Theodore" Logan enterprises Ted "Theodore" Logan and William "Bill" S. Preston enterprises
Token Link Legal Eagle attorney at law Legal Eagle (2017) attorney

Token Link

While Fellegi-Sunter in combination with traditional string distance metrics is highly useful, it has several possible deficiencies:

  • For columns that have categorical levels and are not evenly distributed, only the average match rate is considered for the u parameter. Consider matching the city column with the value "Williamstown", it carries much more information than matching the "Toronto" value.
  • Most string distance algorithms work on the character level. They assume that semantic distances are some functions of the characters composing a string, while in both English and French, the information conveyed to the readers is at the word level.

The Token Link algorithm and R package fix the above issues. It can help with the identification of records where multiple categorical levels are present. It can also identify where columns exist with multiple words in the same column such as company name or address.

The basic algorithm involves:

  1. Tokenize the words in the column, count the occurrences of each token in the dataset.
    Figure 2: Tokenized words in each column
    Description - Figure 2: Tokenized words in each column
    Tokenized words in each column - Original sample dataset
    id Address
    1 742 Evergreen Terrace Springfield
    2 19 Plympton St, Springfield
    3 744 Evergreen Terr, Springfield
    4 100 Industrial Way Springfield

    Clean and Tokenize

    Tokenized words in each column - Sample dataset with counted tokens

    id

    Token

    1

    742

    1

    Evergreen

    1

    Terrace

    1

    Springfield

    2

    19

    2

    Pympton

    2

    Street

    2

    Springfield

    3

    744

    3

    Evergreen

    3

    Terrace

    Count Tokens

    Tokenized words in each column - Sample dataset with counted tokens

    Token

    N

    Springfield

    24

    Evergreen

    12

    Terrace

    12

    Plympton

    6

    Industrial

    4

  2. Repeat tokenization and counting procedure for alternate dataset
  3. Create a full outer join on the tokens of the two-word counts
    Sample dataset 4
    Token N_a N_b U_prob
    Springfield 24 7500 3.7%
    Evergreen 12 2 0.0005%
    Terrace 12 500 0.12%
    Plympton 6 1 0.00013%
    Industrial 4 8 0.00067%
  4. Use this to estimate the U probability for each token. Where nta and ntb are the number of occurrences of the token t in dataset a or b, and Na and Nb are the number of records in dataset a and b.
    Ut=nta*ntbNa*Nb
  5. Estimate the m probability either as a whole or independently for each token.
  6. Join the merged token count file with the original two datasets, calculating PR|Ti-1Nt the probability that any two records are the same given that they have a token in common.
    PR|Ti-1Nt=t=1Ntmt*PRt=1Ntmt*PR+t=1Ntut*1-PR

The technique outlined here can be extended to multiple columns without much difficulty. It can also be integrated with traditional record matching algorithms by using their posterior output as the prior.

Some of the limitations to the Token Link technique:

  • Like all methods related to the Fellegi-Sunter algorithm, it assumes the independence of each piece of information. Token link assumes the independence of words. For example, "research and development" commonly occur together and should not be treated as independent, but this algorithm would treat these words as independent and distinctive units.
  • This algorithm does not consider word order. So "Bill and Ted" would be seen as identical to "Ted and Bill".
  • It has a difficult time finding matches if a simple misspelling occurred in an important identifying word. For instance, the pair "Starbucks coffee" and "Starbacks Coffee" records might be harder for this algorithm to find while "Starbucks coffee" and "Starbucks Caffee" would be easier to find.

To learn more about this technique, more information can be found at TokenLink on GitHub.

How to get started

Statistics Canada's LFE offers support to users and partners for their research and reporting on a cost recovery basis. For more information on this service, connect with the LFE team.

Departments wanting to extract value using linked data about their regulated parties should keep three things in mind.

Unique Identifiers

Consider collecting unique identifiers such as business number from your regulated parties. While it is possible to link data without unique identifiers through attributes like company name or address, these can lead to errors in the linking process. The error rate is often linked to the data quality and the data collection mechanism.

Summary Statistics

Consider which summary metric to request. If there is a chance of error in the linking process, some summary metrics are more robust than others to outliers. Consider requesting the median and interquartile range as measures of central tendency and variation rather than the arithmetic means and standard deviation as the former is more robust to outliers than the latter.

Granularity and Data Size

Consider the potential for data suppression. If a department requests the data be summarized at a very granular level and they do not have a large number of regulated parties, cells in a summary table could be suppressed to protect the privacy of the entities and comply with the Statistics Act. In general, the larger the datasets, the finer the aggregation of the data can be.

Acknowledgments

Entrepreneurship and Linkable File Environment team at Statistics Canada; Zhuo (Sarah) Zhang, Robert Dorling, Department of Fisheries and Oceans Canada

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Date modified:

Notice of release of the Classification of Instructional Programs (CIP) Canada 2021 Version 1.0

Structural Revision

The Classification of Instructional Programs (CIP) Canada 2021 Version 1.0 is released. CIP Canada 2021 Version 1.0 replaces CIP Canada 2016. This version represents the ten-year structural revision to this standard classification, which is used to classify instructional programs according to field of study.

The Generic Statistical Information Model (GSIM) has been used for this revision to identify the types of changes made to the classification: real changes and virtual changes. Real changes are those affecting the scope of the existing classification items or categories, whether or not accompanied by changes in the title, definition and/or the coding. Virtual changes are those made in coding, titles and/or definitions, while the meaning or scope of the classification item remains the same.

The classification revision includes structural changes, clarifications of titles and definitions, changes to examples and exclusions, and the creation of new classification items.

CIP Canada 2021 Version 1.0 reflects various changes and improvements, such as the move of Veterinary instructional programs to Series 01 - Agriculture and veterinary sciences/services/operations and related fields from Series 51 - Health professionals and related programs, as well as the move of medical doctor residencies/fellowships from Series 60 - Health professions residency/fellowship programs to a new Series of their own, Series 61 - Medical residency/fellowship programs. There has also been a significant addition of 73 subseries and 438 instructional program classes in emerging fields of study.

For more information on the Classification of Instructional Programs (CIP) Canada, please visit: Classification of Instructional Programs (CIP) Canada 2021 Version 1.0.

For questions related to the Classification of Instructional Programs (CIP) Canada, please send an email to: statcan.csds-standards-education-cnsd-normes-education.statcan@statcan.gc.ca.

Date modified:

Statistics Canada is seeking input on the new Census of Environment program

Opened: November 2022
Updated: March 2025

Consultative engagement objectives

Canadians are increasingly concerned about the economic, social and health risks and impacts posed by climate change and other environmental issues. These changes are reflected in Canada's ecosystems— like our coastal areas, wetlands, forests, lakes and prairies —where all living things (plants, animals) and non-living things (rocks, water) function together as a unit to make up a community of life.

Statistics Canada has been asked by the Government of Canada to develop a Census of Environment that will provide a robust picture of Canada's ecosystems and their benefit to our well-being and the economy. It will catalogue ecosystems in Canada, tracking their size and condition over time and measuring the ecosystem services provided such as clean air, food and recreation. This important program will inform decisions that will help protect, rehabilitate, enhance and sustain our environment and provide the information needed to understand the benefits of Canada's ecosystems.

How to get involved

Statistics Canada will be further engaging with Canadians in 2025-2026.

Individuals who wish to obtain more information on this engagement initiative may contact us by email at consultativeengagement-mobilisationconsultative@statcan.gc.ca.

Statistics Canada is committed to respecting the privacy of participants. All personal information created, held or collected by the agency is protected by the Privacy Act. For more information on Statistics Canada's privacy policies, please consult the privacy notice.

Results

Summary results of the engagement initiatives will be published online when available.

Table of contents

Introduction

The Privacy Act gives Canadian citizens and people living in Canada the right to access their personal information being held by federal government institutions. The Act also protects against unauthorized disclosure of that personal information and it strictly controls how the government collects, uses, stores, discloses, and disposes of any personal information.

The Annual Report on the Administration of the Privacy Act is prepared and submitted, in accordance with section 72 of the Act, and it covers the period from April 1, 2021, to March 31, 2022. The report is tabled in Parliament.

Administration of the Privacy Act

The Privacy Act, which concerns itself with personal information, stipulates that government institutions can collect personal information only if it relates to the operation of programs or activities of these institutions. In the case of Statistics Canada, the Statistics Act provides the authority to collect personal information. In addition, institutions are required to protect the collected information from disclosure.

The Director of the Office of Privacy Management and Information Coordination administers the Access to Information and Privacy legislations within Statistics Canada, and is also the Access to Information and Privacy (ATIP) Coordinator and Chief Privacy Officer for the Agency.

Organization and mandate of Statistics Canada

Statistics Canada's mandate derives primarily from the Statistics Act. The Act requires that the Agency collect, compile, analyze and publish statistical information on the economic, social, and general conditions of the country and its citizens. The Act also requires that Statistics Canada coordinate the national statistical system, in particular, to avoid duplication in the information collected by government. To this end, the Chief Statistician may enter into joint data collection or sharing agreements with provincial and territorial statistical agencies, as well as with federal, provincial and territorial government departments, pursuant to provisions of the Act.

The Statistics Act specifically requires Statistics Canada to conduct a Census of Population and a Census of Agriculture every five years as it did in 2021. The Act also gives the Agency substantial powers to request information through surveys of Canadian businesses and households. Under the Act, the Chief Statistician determines whether a survey will be mandatory or voluntary. Statistics Canada has generally made voluntary household data collection other than the Census of Population and the Labour Force Survey, as the latter produces key economic data. The Census of Agriculture and most other business surveys are mandatory. Refusal to participate in a mandatory survey is subject to legal penalties.

By law, Statistics Canada can also access administrative records, including personal and business tax data, credit information, customs declarations, and birth and death records. Such records are critical sources of statistical information that enable the Agency to reduce the reporting burden on businesses and individual respondents. Statistics Canada is considered a leader among the world's statistical agencies in reducing reporting burden by using administrative data.

Statistics Canada is ensuring that privacy protection methods and protocols continue to evolve as new data sources with varying levels of sensitivity emerge. The Necessity and Proportionality framework was implemented to ensure increasing transparency in the data acquisition process, to provide stronger justification (necessity) for data acquisition, and to be more explicit about the efforts used to gather data in a manner that is both efficient and proportional to its necessity and sensitivity. This includes ensuring that necessity (requirement for data or information) is well-defined; applying the scientific approach and a series of checkpoints on sensitivity, ethics and proportionality (quality, sample size, content and risk mitigation); considering alternative methods; and requiring a privacy impact assessment and communication throughout the process to ensure transparency.

Statistics Canada adopted a Responsible Privacy approach to honour the commitment made to Canadians to protect their personal information. These mechanisms help Statistics Canada to fulfill this commitment while ensuring that Canadians have all the key information on Canada's economy, society and environment that they require to function effectively as citizens and decision-makers in a rapidly evolving world.

Delegation instrument

The delegation instrument exercises the powers and functions of the Minister as the head of a government institution, pursuant to section 73 of the Privacy Act. The current detailed list of authorities under the Privacy Act has been formally delegated by the Minister of Innovation, Science and Economic Development as of May 18, 2021, (Appendix A) and provides full delegated authority to the Director and Assistant Director of the Office of Privacy Management and Information Coordination.

Resources

The Access to Information and Privacy (ATIP) Office operates within an allocation of 4.5 persons/year. One ATIP Manager, two Senior ATIP analysts, and two ATIP analysts work full time on the processing of requests.

Statistical report

The statistical report provides aggregate data on the application of the Privacy Act. This information is made public annually and is included with the annual report (Appendix B).

Implementation: Privacy

The Privacy Act has a substantial impact on Statistics Canada, but the impact cannot be measured only by the number of requests processed. Although society seeks a broader range of detailed information, it also demands more accountability on the part of government about the collection of personal information and the purposes served by the information.

The Agency has a strong track record of respecting the privacy of Canadians and has taken a number of initiatives to address the privacy challenges this dichotomy raises.

Statistics Canada has internal directives that reflect the basic principles found in the Privacy Act. The Agency's Directive on Informing Survey Respondents requires that all respondents be informed of the expected use of the statistics produced from the survey results, the authority under which the survey is taken, their obligation to respond, the confidentiality protection given to all information collected under the Statistics Act, and any data-sharing arrangements pursuant to provisions of the Statistics Act.

Statistics Canada also developed the Directive on Microdata Linkage to respond to concerns of both respondents and privacy advocates on the potential of matching an individual's information gathered from a variety of sources.

These two directives not only support compliance with the letter and the spirit of the Privacy Act, but also demonstrate the Agency's commitment to the protection and appropriate use of the personal information under its control, while still meeting its mandate.

The Agency has also developed and implemented a Necessity and Proportionality framework that ensures that any collection of personal information for its statistical programs is duly justified.

As we chart new paths and methods of collecting data, respecting and protecting the rightful privacy of Canadians sit at the heart of everything we do. Statistics Canada's Trust Centre underlines how we meet Canadians' information needs while keeping their data safe and private.

Recent unexpected events such as the pandemic and current societal changes (political, legislative, social and technological) are challenging Statistics Canada to adapt and lead as we continue our modernization journey and as we strive to meet the demands of a digital world in the 21st century.

Statistics Canada continues to work diligently to ensure that the confidentiality it has committed to in law and in principle, is upheld. This includes ensuring that privacy remains at the forefront of all our activities.

In the new reality of instant information over social media, meeting legal requirements is no longer sufficient. Institutions must pro-actively engage with Canadians regarding what is socially acceptable under a social contract.

Statistics Canada's very mandate requires that it produce information that helps Canadians better understand their country – its population, resources, economy, environment, society and culture. To achieve this, the Agency must collect a considerable amount of personal information directly from Canadians through surveys, or indirectly from private and public organizations. Parliament has given Statistics Canada this mandate to better serve Canadians, but with such authority comes great responsibility. Statistics Canada continually adjusts to new realities and adapts existing mechanisms, or develops new ones to protect Canadians' privacy and ensure that their data will not be misused. The Agency must demonstrate and provide assurances to Canadians that it can be trusted with their information.

As Statistics Canada continues to modernize, it is committing to Responsible Privacy. Responsible Privacy is instrumental in honouring our promise to diligently collect, use, disclose and protect Canadians' personal information. It ensures that we indefatigably strive to go beyond what is required, and encompasses innovative privacy checks and balances that ensure due diligence when handling personal information. It requires that privacy be imprinted in all our activities.

To foster the Responsible Privacy approach and meet the demands of a digital world in the 21st century, senior management at Statistics Canada has committed to a formalized Privacy Management Program (PMP).

Privacy Management Program

Image
Privacy Management Program
Description - Privacy Management Program

Statistics Canada

Privacy Management Program 

Oversight & Review

Assess & Revise

Program Controls as neccessary

Program Controls

Personal information inventory

Easy access by Canadians to their personal information

Directives, Policies & Procedures

Streamline governance to align with responsible privacy

Risk Assessments & Other Supporting Tools

Modernize Privacy Toolbox & streamline PIAs

Training, Education & Awareness

Educating Canadians on privacy in the statistical context

Breach & Incident Management Response Protocols

Simplified self-help kit/resources for staff; Active Monitoring

Client, Partner & Data Provider Management

Early intervention logic model & privacy triggers

External Communication

Modernized Privacy Portal

Organizational Commitment

Buy-in from the Top

Chief Privacy Officer

Office of Privacy Management (experts)

Reporting

While many of its components were already part of the Agency's regular activities, the PMP instils a systematic and strategic approach that reinforces our commitment to Canadians regarding their personal information.

Privacy requests

Disposition of requests completed

  • All disclosed: 9
  • Disclosed in part: 5
  • Nothing disclosed (exempt): 0
  • Does not exist: 15
  • Abandoned: 36
  • Total: 65

The Agency received 161 new requests in 2021-2022 and 36 requests were carried over from the previous reporting period. During this period, 65 requests were completed and 132 requests were carried forward to the next reporting period.

For 9 requests, information was disclosed completely and for 5 requests, information was partially disclosed, having redactions applied to protect personal information pertaining to other individuals. For 15 requests, the information did not exist, and 36 requests were abandoned as applicants did not respond to requests for additional information or chose to withdraw them entirely. The public is the largest privacy client group for Statistics Canada.

In addition to requests from the general public, the Agency receives requests from current and former federal public servants regarding personal or staff relations issues. Statistics Canada responds to a number of requests for personal information through its pension search program. This program provides members of the public with information from their own census records, and from the 1940 National Registration records, to support their applications for pensions, citizenship, passports and other services when other administrative records, such as birth certificates, are required but no longer exist or were never issued. Regulations permit duly authorized representatives to act on behalf of a minor or an incompetent person to administer their affairs or estate. To do so, the trustees and estate administrators seek personal information from the census or from 1940 national registration records of deceased individuals, minors, or dependent adults. In the case of the deceased, the administrator of the estate may exercise these rights, but only for the purposes of estate administration.

For the 2021-22 fiscal year, and in relation to the 2021 Census of Population, of the 161 new Privacy requests received, 81 were related to individuals requesting copies of their completed census questionnaires. It should be noted as well that, of the 132 requests carried over to the next fiscal year, 81 of those are due to the fact that extracts of the 2021 Census of Population information, are not yet available for distribution.

Responding to privacy requests involved reviewing more than 1,744 pages, of which 1,416 pages were released. Fourteen (14) requestors received information electronically by email or e-post and zero (0) requestors received the information in paper format.

Privacy requests
Fiscal Year Requests Received Requests Completed Number of Pages Processed Number of Pages Released
2021/2022 161 65 1,744 1,416
2020/2021 86 138 4,076 2,983
2019/2020 283 210 5,586 3,364
2018/2019 1,012 1,007 15,244 13,595
2017/2018 157 148 20,216 10,886

Other requests

During this period, Statistics Canada did not receive any Privacy Act consultation requests from other departments.

Disposition of completed requests

The disposition of the 65 requests completed in 2021-2022 was as follows:

  • 9 were fully disclosed (19%)
  • 5 were disclosed in part (3%)
  • 15 information did not exist (12%)
  • 36 were abandoned by applicants (66%)

Completion time and extensions

In 2021-2022 the number of privacy requests completed was 65 for an average of 313 over the last five years. Over half of all completed requests in 2021-22 (35 requests or 54%) processed in 2021-2022 were within the time period and as prescribed by the Act. Several factors contributed to the timely response; information and training sessions with senior leaders and sector contacts, and a streamlined delegation order. There were no extensions taken.

The 65 requests completed in 2021-2022 were processed in the following time frames:

  • 20 within 1 to 15 days (31%)
  • 15 within 16 to 30 days (23%)
  • 6 within 31 to 60 days (9%)
  • 2 within 61 to 120 days (3%)
  • 6 within 121 to 180 days (9%)
  • 11 within 181 to 365 days (17%)
  • 5 more than 365 days (8%)

Due to the exceptional measures taken to curb the spread of COVID-19 and to protect federal employees, Statistics Canada employees have been operating with significantly-reduced on-site workforces since April 2020. This impact brought forward new electronic changes to procedures that were implemented in order to facilitate the processing of requests remotely.

Exemptions invoked

In 2021-2022, one exemption was invoked as per the Privacy Act, which was as follows:

  • Section 26: Exempting personal information about individuals other than the requestor (5).

Costs

During 2021-2022, the ATIP Office incurred an estimated $79,421 in salary costs and 0$ in administrative costs to administer the Privacy Act. With the introduction of Statistics Canada's return to work place plan entitled "virtual-by-design environment" the ATIP division has been able to reduce administrative costs for the fiscal year 2021-22 by reducing the use of paper, completing virtual training courses, lowering the cost of travel and reducing the costs of office supplies.

Training initiatives for privacy

In 2021-2022, the Access to Information and Privacy (ATIP) Office began developing a formal training program for all staff across the Agency, which began in April 2020. Informal one-on-one training was made available, until such time as the formal training was implemented. The informal training assists staff in understanding their obligations under the Act, as well as informs them about policies and directives related to personal information at Statistics Canada.

Statistics Canada's Office of Privacy Management and Information Coordination offers courses on a variety of subjects related to the Statistics Act and the Privacy Act as well as supporting policies and directives. These include sessions on "Privacy Impact Assessment" and "Privacy and Confidentiality", with a focus on personal information collected about employees of Statistics Canada, clients or the public, and appropriate use of such personal information.

Statistics Canada also requires employees to complete computer-based courses on confidentiality. A mandatory course for new employees offers a brief overview of confidentiality, illustrating its importance at the Agency.

Policies, guidelines and procedures

The ATIP Office has a variety of tools in place to ensure that ATIP sector contacts are well informed about their roles and responsibilities for coordinating privacy requests. These tools include a concise checklist outlining steps to follow when providing responsive records for privacy requests, and a responsible contact from the ATIP team throughout the process. There are also a variety of directives and policies provided by the Treasury Board Secretariat, about the protection of personal information. Personal and confidential information is protected by the Privacy Act and the Statistics Act and will only be disclosed as permitted by these Acts.

Statistics Canada developed and published a privacy framework that identifies the full scope of privacy controls within the operations of Statistics Canada as a collection of approved practices, procedures and governance related to privacy. This includes the identification of the Director, Office of Privacy Management and Information Coordination, as the Chief Privacy Officer (CPO) for Statistics Canada, as designated by the Chief Statistician. The CPO provides leadership on matters related to privacy, develops business strategies and processes that ensure that privacy is considered and accounted for in business decision, and ensures the safeguarding of the information through administrative policy instruments and best practices.

Given its unique position in the federal government in collecting personal information solely for statistical and research purposes, Statistics Canada has determined that the privacy issues associated with its statistical activities undertaken under the authority of the Statistics Act could be addressed by means of a Generic Privacy Impact Assessment (PIA).

Although the Generic PIA is comprehensive and reflects the vast majority of Statistics Canada's operations, in the instance of extraordinary activities, specific PIAs are conducted with input from the Office of the Privacy Commissioner (OPC). Statistics Canada prepares supplements to the Generic PIA for all new and significantly redesigned surveys and statistical programs involving the collection, use or disclosure of personal information that raise unique or additional privacy, confidentiality or security risks that have not been addressed in the Generic PIA.

Complaints and investigations

There was one (1) time delay complaint made against Statistics Canada lodged with the OPC. The ATIP Office has responded to the complaint as identification was missing at the time from the complainant, and while the investigation has not yet been finalized, review of the records is on-going.

Monitoring of the requests

At Statistics Canada, the ATIP Office processes and monitors requests by registering them in a comprehensive system known as Privasoft – Access Pro Case Management. An acknowledgement of the request is sent to the client and a retrieval form is forwarded to the relevant program area, Office of Primary Interest (OPI), for responsive records. If the OPI and/or the ATIP Office need to clarify the request, the ATIP Office contacts the client.

The retrieval form was created by the ATIP Office at Statistics Canada and is based on the Policy on Privacy Protection and the Directive on Privacy Practices from the Treasury Board Secretariat. The form includes the text of the request, the name and phone number of the ATIP Officer, and the date by which records are required (normally 5 to 10 days). The form states that the ATIP Office is obligated to report annually on the administrative costs related to requests and thus information is needed on the group(s) and level(s) of those involved in the retrieval process, and the amount of time spent working on the request (including time for search, retrieval, internal review (relevant or not to the request) and photocopying). The individuals providing the records are asked to identify any areas which may be sensitive in nature (e.g., personal information, legal issues), and the Director General or responsible delegate of the program area signs the form.

The ATIP Office assists the program areas with the retrieval of records from day one. As 5 to 10 days are allowed for the retrieval, a follow-up is made on the fifth day. If additional time is required for the retrieval, this is when the program area is to notify the ATIP Office. An additional 1 to 5 days may be granted depending on the amount of work remaining. Once the documents are received from the OPI, the ATIP Office ensures the form is duly completed and that it has been signed by the appropriate manager. The ATIP Office takes 5 to 10 days to review and process the records. Once the work from the ATIP Office is completed, the final version is released to the client. The OPI and management are very aware of the importance of ATIP requests.

Privacy breaches

The Privacy and Information Breach Protocol provides clear identification of the various roles and responsibilities in the event of a breach. It includes the requirement to complete a standard template which incorporates the elements suggested in the Treasury Board Secretariat's guidelines on how to respond to a privacy breach. The template has been approved by the Agency's senior management. At a minimum, the incident report will contain the following information:

  • a description of the incident (who, what, when, where, why, how)
  • the actions already taken and planned for the future
  • a description of the risks/impacts
  • any other information that might be helpful in locating any lost item(s) or in assessing the consequences of loss or compromise
  • recommendations for reducing or eliminating the risk of the event reoccurring in future
  • information on whether the individuals or organizations whose information was breached were informed of the incident
  • indication if the individuals, Office of the Privacy Commissioner (OPC) and Treasury Board Secretariat will be informed of the incident and if not, rationale for not informing them.

Best practices to eliminate or reduce future recurrences that are identified during an investigation must be communicated to other employees to prevent a recurrence of the breach.

Breaches are coordinated by a centralized group to ensure that all programs impacted by the breach provide input.

There were 18 privacy breaches at Statistics Canada during the reporting period, of which 3 were material in nature. A total of 410 people were affected by these 18 breaches. Amongst the 410 people affected, 200 were a result of 1 incident related to employment candidates email information that was not material in nature.

Three material breaches were reported to the OPC, affecting a total of 5 individuals:

  • A Census Enumerator's vehicle was stolen including two completed Census long-form questionnaires.
  • Two completed Census long-form questionnaires were stolen from a Census Enumerator's home during a break-in.
  • A minor's name was erroneously disclosed through an invitation letter to participate in a Statistics Canada survey.

Additional measures, specific to the areas which experienced a breach were implemented, including the following:

  • retraining of Census Enumerators on proper storage of Census materials;
  • exploring and updating methodologies for the creation of survey frames for all surveys involving children.

Privacy impact assessments

The Statistics Canada Directive on Conducting Privacy Impact Assessments (PIAs) specifies the roles and responsibilities of its senior managers and privacy specialists with regard to the collection, use and dissemination of personal information. This directive applies to all statistical and non-statistical programs that engage in the collection, use or disclosure of personal information.

Statistics Canada's Generic PIA covers all aspects of the Agency's statistical programs that collect, use and disseminate information in support of the mandate under the Statistics Act. The Generic PIA addresses the ten privacy principles, and includes a threat and risk assessment for various collection and access modes.

Supplements to the Generic PIA are produced for new and significantly redesigned collections, uses or disclosures of personal information that raise unique or additional privacy, confidentiality or security risks. The Generic PIA and its supplements are posted on the Statistics Canada website: Generic privacy impact assessment.

Specific PIAs are also conducted for new or redesigned administrative programs and services that involve the collection, use and disclosure of personal information that are not addressed in the Generic PIA. Summaries of completed privacy impact assessments can be found on the Statistics Canada website: Privacy impact assessments.

In the current reporting period, 6 PIAs and 10 supplements were approved and submitted to the Office of the Privacy Commissioner and the Treasury Board Secretariat. The following are brief descriptions:

Client Relationship Management System

A PIA was conducted to determine if there were any privacy, confidentiality or security issues associated with updates to Statistics Canada's Client Relationship Management (CRM) system. Statistics Canada has been leveraging a Client Relationship Management (CRM) solution to help support the provision of client service delivery, business respondent relations, microdata access and Census respondent relations. The CRM system was updated to adapt to new realities and to support a strategic, holistic and consistent approach to the collection of quality client business intelligence data that can help to strategically respond to clients' needs and better serve Canadians. The assessment did not identify any privacy risks that cannot be managed using existing safeguards.

Employee Wellness Surveys and Pulse Check Surveys

A PIA was conducted to determine if there were any privacy, confidentiality or security issues associated with the Employee Wellness Surveys and associated Pulse Check Surveys. These internal surveys are administered only to Statistics Canada and Statistical Survey Operations employees and seek to offer up-to-date and representative measurement of the state of Statistics Canada's psychological health and safety. The results help the organization better understand where challenges to psychological health and safety reside, where resources to help bolster psychological health and safety exist, and how to best improve overall psychological health and safety, and ultimately, performance. The assessment did not identify any privacy risks that cannot be managed using existing safeguards.

Engaging Disability Innovation Study

A PIA was conducted to determine if there were any privacy, confidentiality or security issues associated with the Engaging Disability Innovation Study which consists of the quantitative Employment and Accessibility Survey and associated qualitative asynchronous online engagement. This internal study is conducted only with Statistics Canada and Statistical Survey Operations employees. It aims to help Statistics Canada's Accessibility Secretariat understand where challenges of accessibility and safety reside, where resources to help bolster accessibility exist, and how to best improve overall accessibility of Statistics Canada's recruitment, retention and promotion process, operational practices, and ultimately, employee performance. The assessment did not identify any privacy risks that cannot be managed using existing safeguards.

Meltwater: Social Media Communications Tool

A PIA was conducted to determine if there were any privacy, confidentiality or security issues associated with Statistics Canada's use of the Meltwater Social Media Communications Tool. The tool serves to search, monitor and analyze social media and traditional media traffic on issues and topics relevant to Statistics Canada. Using Application Programming Interfaces (APIs), Meltwater performs searches of social and traditional media content based on specific search query keywords relevant to the agency's mandate, indexes the related information found and then presents the results to the agency. The use of Meltwater allows the Agency to better understand current opinion, sentiment and overall conversation on specific Statistics Canada issues to create communications products that resonate with target audiences. While information publicly posted by social media users could include information such as profile picture, comments or opinions, personal preferences or interests, only information pertinent to public relations and communications are retained and used, and are never disseminated in identifiable format. The reports generated through Meltwater only include information in aggregate non-identifiable form. The assessment did not identify any privacy risks that cannot be managed using existing safeguards.

Microsoft 365

A PIA was conducted to determine if there were any privacy, confidentiality or security issues associated with the implementation of Microsoft 365. Microsoft 365 is an enterprise-level, cloud-based version of the Microsoft office productivity tools for creating documents, presentations, and spreadsheets, for internal communications, for managing emails, for work planning, and for other common administrative tasks. This integrated suite of tools supports the daily activities of Statistics Canada's employees, including collaboration within the organization. The assessment did not identify any privacy risks that cannot be managed using existing safeguards.

Vitali-T-Stat Mobile Application

A PIA was conducted to determine if there were any privacy, confidentiality or security issues associated with the Vitali-T-Stat Mobile Application. Statistics Canada developed and implemented a mobile application as a new means of inviting respondents to access the agency's secure survey collection infrastructure and complete a survey. The application itself does not collect any personal information; it simply prompts respondents and points them to the secure collection environment housed at Statistics Canada where they complete the survey questionnaire. The application does not utilise geo-location tracking, camera or microphone access, calendar integration, barcode scanning or beacon technology. It will first be used in the context of the longitudinal Pilot Study on Everyday Well-being which will collect data on the well-being of Canadians, and for which a separate supplement to Statistics Canada's Generic PIA supplement was developed. The assessment did not identify any privacy risks that cannot be managed using existing safeguards.

2021 Census of Population

A supplement to the Generic PIA was conducted to determine if there were any privacy, confidentiality or security issues associated with new content for the 2021 Census of Population. The Census of Population's purpose is to provide statistical information, analyses and services that measure changes in the Canadian population and demographic characteristics. It serves as a basis for public and private decision making, research and analysis in areas of concern to the people of Canada. Under the Statistics Act (R.S.C., 1985, c. S-19), Statistics Canada is responsible for conducting the Census of Population every five years. As in past censuses, extensive consultations on the questions to include in the 2021 Census of Population were held with Canadians. New and modified questions, developed to reflect new needs identified in the consultations, were qualitatively tested by Statistics Canada in 2018. The assessment concluded that, with the existing Statistics Canada safeguards, any remaining risks are such that Statistics Canada is prepared to accept and manage the risk.

Canadian Child Welfare Information System

A supplement to the Generic PIA was conducted to determine if there were any privacy, confidentiality or security issues associated with the Canadian Child Welfare Information System. The CCWIS is a national public health information system on child welfare, and its purpose is to support nationally standardized analyses and reporting on child maltreatment; investigations and outcomes; the number of children in need of protection; and passage through the child welfare system, including referral to services, placement in foster care, connections to family, reunification, and other requests for family services. Data on these issues inform regional and national child welfare prevention and protection policies and practices. Data-informed child welfare is crucial to protect and improve the lives of many Canadian children and their families. The assessment concluded that, with the existing Statistics Canada safeguards, any remaining risks are such that Statistics Canada is prepared to accept and manage the risk.

Supplement to the Canadian COVID-19 Antibody and Health Survey for Cycle 2

A supplement to the Canadian COVID-19 Antibody and Health Survey was conducted to determine if there were any privacy, confidentiality or security issues associated with Cycle 2 of the survey. The content of the Cycle 2 questionnaire is slightly different, and includes, in addition to gathering information on COVID-19 status and related health concerns, questions on use of the health care system, prescribed medications, active infections (nucleic acid-based testing) and previous infections (antibody testing). Participants may also be asked to participate in a self-administered collection of microbial nucleic acids from saliva. The collected specimen would be used to assess current SARS-CoV-2 infection status via a polymerase chain-reaction (PCR) test. Only with informed consent from respondents, results from the PCR test are sent to the respondents and local health authorities may be notified when results are positive. All other personal information collected is the same as in the previous cycle of the survey. The assessment concluded that, with the existing Statistics Canada safeguards, any remaining risks are such that Statistics Canada is prepared to accept and manage the risk.

Canadian Human Trafficking Hotline Feasibility Study Data Acquisition Project

A supplement to the Generic PIA was conducted to determine if there were any privacy, confidentiality or security issues associated with the Canadian Human Trafficking Hotline Feasibility Study Data Acquisition Project. In response to the National Strategy to Combat Human Trafficking's call for enhanced data to help inform policy and programs that help victims and survivors, Statistics Canada is working with the Canadian Centre to End Human Trafficking to acquire and examine administrative data related to their operation of the Canadian Human Trafficking Hotline. The hotline has specific procedures in place to seek consent from callers and to inform why and how their information will be used. No information that directly identifies a victim or caller will be provided to Statistics Canada, and the agency will not publish any information that could potentially identify an individual based on the characteristics of victims or location of incidents. The assessment concluded that, with the existing Statistics Canada safeguards, any remaining risks are such that Statistics Canada is prepared to accept and manage the risk.

Childhood National Immunization Coverage Survey

A supplement to the Generic PIA was conducted to determine if there were any privacy, confidentiality or security issues associated with the Childhood National Immunization Coverage Survey. The main objectives of this survey are to determine if children are being vaccinated in accordance with the recommended immunization schedules for publicly-funded vaccines and to measure to what degree recent public health recommendations are being adopted to increase vaccination against the flu and pertussis during pregnancy. Results help health authorities focus vaccination campaigns for the under-vaccinated and vulnerable populations. Results also allow Canada to meet its commitment to provide the World Health Organization and the Pan American Health Organization with estimates of national coverage for childhood vaccines such as measles, diphtheria, pertussis, tetanus and polio. For the 2021 cycle, questions were added to help understand the impact the COVID-19 pandemic has had on immunization and vaccine coverage for children and pregnant women. The assessment concluded that with the existing Statistics Canada safeguards, any remaining risks are such that Statistics Canada is prepared to accept and manage the risk.

Update to the Longitudinal Immigration Database

A supplement to the Generic PIA was conducted to determine if there were any privacy, confidentiality or security issues associated with updates to the Longitudinal Immigration Database. The Database was implemented in 1997, and integrates immigration and citizenship data provided by Immigration, Refugees and Citizenship Canada with tax information provided by the Canada Revenue Agency. It is used for statistical research on the socioeconomic performance of non-permanent residents and immigrants in Canada, and supports public policy development on population migration, cultural diversity and the challenges of immigrant integration. The Database originally only included permanent resident data for immigrants admitted since 1980, and did not include information on non-permanent residents. With this update to the Database, coverage has been expanded to include immigrants admitted since 1952, and non-permanent residents. Statistics Canada only releases anonymized, aggregated statistical information on immigrants and non-permanent residents. Individuals will not be identifiable in any product disseminated to the public. The assessment concluded that with the existing Statistics Canada safeguards, any remaining risks are such that Statistics Canada is prepared to accept and manage the risk.

Mental Health and Access to Care Survey

A supplement to the Generic PIA was conducted to determine if there were any privacy, confidentiality or security issues associated with the Mental Health and Access to Care Survey. This voluntary survey collects information about the mental health status of Canadians, as well as their access to and need for services and support, whether formal or informal. It also assesses the impact of the COVID-19 pandemic on population health as well as evaluate changes in patterns of mental health, service use and functioning in the last ten years. Results help inform government decision‐making and policy development in order to support vulnerable Canadians and their families dealing with mental health issues. Survey results regarding the unmet need for mental-health services also help guide decisions about which parts of the mental-health services system need to be improved, where awareness and treatment programs are most needed, and how such targeted treatment programs should be developed. The assessment concluded that with the existing Statistics Canada safeguards, any remaining risks are such that Statistics Canada is prepared to accept and manage the risk.

Pilot Study on Everyday Well-Being

A supplement to the Generic PIA was conducted to determine if there were any privacy, confidentiality or security issues associated with the Pilot Study on Everyday Well-Being. Canadians who opt to participate in this voluntary pilot study are asked to download Statistics Canada's mobile application (Vitali-T-Stat) and customize their setting to receive up to a maximum of five prompts a day over a thirty day period. Upon receiving and accepting a prompt, respondents are redirected to Statistics Canada's secure collection infrastructure and the Pilot Study on Everyday Well-being questionnaire that asks in-the-moment questions about their activities and feelings. The app itself, for which a PIA was conducted, does not collect any personal information. The results are used to fill key gaps in national-level subjective well-being and can inform governments' decisions regarding publicly-funded cultural and other programs that contribute to Canadians' well-being. The assessment concluded that with the existing Statistics Canada safeguards, any remaining risks are such that Statistics Canada is prepared to accept and manage the risk.

Survey of Employees under Federal Jurisdiction

A supplement to the Generic PIA was conducted to determine if there were any privacy, confidentiality or security issues associated with the Survey of Employees under Federal Jurisdiction. This voluntary targeted survey collects information on the quality of employees' work conditions, access to benefits and flexible work arrangements, labour relations, work-related well-being and workplace health and safety including harassment and discrimination. The information from this survey guides research and analysis to update the Canada Labour Code. The assessment concluded that with the existing Statistics Canada safeguards, any remaining risks are such that Statistics Canada is prepared to accept and manage the risk.

Survey on Health Care Workers' Experiences During the Pandemic

A supplement to the Generic PIA was conducted to determine if there were any privacy, confidentiality or security issues associated with the Survey on Health Care Workers' Experiences During the Pandemic. The purpose of this voluntary survey is to understand the impact of the COVID-19 pandemic on health care workers in Canada. It covers topics such as job type and setting, personal protective equipment and infection prevention and control practices and protocols, COVID-19 vaccination and diagnosis, and the impacts of the pandemic on personal health and work life. It also includes general demographic questions. The results of this survey help inform health care workforce planning, the delivery of health care services, and to better understand what health care workers need in terms of equipment, training and support. The assessment concluded that with the existing Statistics Canada safeguards, any remaining risks are such that Statistics Canada is prepared to accept and manage the risk.

Microdata linkage

As outlined in Statistics Canada's Directive on Microdata Linkage, linkages of different records pertaining to the same individual are carried out only for statistical purposes and only in cases where the public good is clearly evident. One of the primary objectives of these linkages is to produce statistical information that facilitates a better understanding of Canadian society, the economy and the environment.

All microdata linkage proposals must satisfy a prescribed review process as outlined in the directive. In addition to demonstrating the public benefit, each submission must provide details of the output. The public dissemination of any information resulting from microdata linkage, like all other statistical information, is only at an aggregate level which protects the confidentiality of the information of individuals.

In 2021-2022, there were 27 approved microdata linkages that involved personal information. A summary of these record linkages is found in Appendix C.

8(2)(m) of the Privacy Act

No disclosures were made under paragraph 8(2)(m) of the Privacy Act during the reporting period.

Appendix A: Delegation Order

Access to Information and Privacy Acts Delegation Order

The Minister of Innovation, Science and Industry, pursuant to section 73 of the Access to Information Act and section 73 of the Privacy Act, hereby designates the persons holding the positions set out in the schedule hereto, or the persons occupying on an acting basis those positions, to exercise the powers and functions of the Minister as the head of Statistics Canada, under the section of the Act set out in the schedule opposite each position. This Delegation Order supersedes all previous Delegation Orders.

Schedule

Schedule
Position Access to Information Act and Regulations Privacy Act and Regulations
Chief Statistician of Canada Full authority Full authority
Chief of Staff, Office of the Chief Statistician Full authority Full authority
Director, Office of Privacy Management and Information Coordination Full authority Full authority
Assistant Director, Office of Privacy Management and Information Coordination Full authority Full authority
Senior Access to Information and Privacy Project Manager Sections: 7(a), 8(1), 9, 11(2), 11(3), 11(4), 11(5), 11(6), 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27(1), 27(4), 28(1)(b), 28(2), 28(4), 68, 69, 71(1)
Regulations:
Sections: 6(1), 7(1), 7(2), 7(3), 8, 8.1
Sections: 8(2)(j), 8(2)(m), 10, 14, 15, 17(2)(b), 17(3)(b), 18(2), 19(1), 19(2), 20, 21, 22, 23, 24, 25, 26, 27, 28, 70
Regulations:
Sections: 9, 11(2), 11(4), 13(1), 14
Senior Access to Information and Privacy Project Manager Sections: 7(a), 8(1), 9, 11(2), 11(3), 11(4), 11(5), 11(6), 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27(1), 27(4), 28(1)(b), 28(2), 28(4), 68, 69, 71(1)
Regulations:
Sections: 6(1), 7(1), 7(2), 7(3), 8, 8.1
Sections: 8(2)(j), 8(2)(m), 10, 14, 15, 17(2)(b), 17(3)(b), 18(2), 19(1), 19(2), 20, 21, 22, 23, 24, 25, 26, 27, 28, 70
Regulations:
Sections: 9, 11(2), 11(4), 13(1), 14
Analyst, Access to Information and Privacy Sections: 7(a), 8(1), 9, 11(2), 11(3), 11(4), 11(5), 11(6), 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27(1), 27(4), 28(1)(b), 28(2), 28(4), 68, 69, 71(1)
Regulations:
Sections: 6(1), 7(1), 7(2), 7(3), 8, 8.1
Sections: 8(2)(j), 8(2)(m), 10, 14, 15, 17(2)(b), 17(3)(b), 18(2), 19(1), 19(2), 20, 21, 22, 23, 24, 25, 26, 27, 28, 70
Regulations:
Sections: 9, 11(2), 11(4), 13(1), 14
Intake Officer, Access to Information and Privacy Sections 7(a), 8(1), 9, 11(2), 11(3), 11(4), 11(5), 11(6), 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27(1), 27(4), 28(1)(b), 28(2), 28(4), 68, 69, 71(1)
Regulations:
Sections: 6(1), 7(1), 7(2), 7(3), 8, 8.1
Sections: 8(2)(j), 8(2)(m), 10, 14, 15, 17(2)(b), 17(3)(b), 18(2), 19(1), 19(2), 20, 21, 22, 23, 24, 25, 26, 27, 28, 70
Regulations:
Sections: 9, 11(2), 11(4), 13(1), 14

The original version was signed by
The Honourable François-Philippe Champagne
Minister of Innovation, Science and Industry
Dated, at the City of Ottawa
May 18, 2021

Appendix B: Statistical Report on the Privacy Act

Name of institution: Statistics Canada

Reporting period: 2021-04-01 to 2022-03-31

Section 1: Requests Under the Privacy Act

1.1 Number of requests recevied

Number of requests recevied
  Number of Requests
Received during reporting period   161
Outstanding from previous reporting periods   36
Outstanding from previous reporting period 35  
Outstanding from more than one reporting period 1  
Total   197
Closed during reporting period   65
Carried over to next reporting period   132
Carried over within legislated timeline 1  
Carried over beyond legislated timeline 131  

1.2 Channels of requests

Channels of requests
Source Number of Requests
Online 109
E-mail 0
Mail 52
In person 0
Phone 0
Fax 0
Total 161

Section 2: Informal requests

2.1 Number of requests received

Number of requests recevied
  Number of Requests
Received during reporting period   0
Outstanding from previous reporting periods   0
Outstanding from previous reporting period 0  
Outstanding from more than one reporting period 0  
Total   0
Closed during reporting period   0
Carried over to next reporting period   0

2.2 Channels of informal requests

Channels of informal requests
Source Number of Requests
Online 0
E-mail 0
Mail 0
In person 0
Phone 0
Fax 0
Total 0

2.3 Completion time of informal requests

Completion time of informal requests
1 to 15 Days 16 to 30 Days 31 to 60 Days 61 to 120 Days 121 to 180 Days 181 to 365 Days More Than 365 Days Total
0 0 0 0 0 0 0 0

2.4 Pages released informally

Pages released informally
Less Than 100 Pages Released 101-500 Pages Released 501-1000 Pages Released 1001-5000 Pages Released More Than 5000 Pages Released
Number of Requests Pages Released Number of Requests Pages Released Number of Requests Pages Released Number of Requests Pages Released Number of Requests Pages Released
0 0 0 0 0 0 0 0 0 0

Section 3: Requests Closed During the Reporting Period

3.1 Disposition and completion time

Disposition and completion time
Disposition of Requests Completion Time
1 to 15 Days 16 to 30 Days 31 to 60 Days 61 to 120 Days 121 to 180 Days 181 to 365 Days More Than 365 Days Total
All Disclosed 4 3 0 1 0 1 0 9
Disclosed in part 0 1 2 0 1 0 1 5
All exempted 0 0 0 0 0 0 0 0
All excluded 0 0 0 0 0 0 0 0
No records exist 5 6 3 0 1 0 0 15
Request abandoned 11 5 1 1 4 10 4 36
Neither confirmed nor denied 0 0 0 0 0 0 0 0
Total 20 15 6 2 6 11 5 65

3.2 Exemptions

Exemptions
Section Number of Requests
18(2) 0
19(1)(a) 0
19(1)(b) 0
19(1)(c) 0
19(1)(d) 0
19(1)(e) 0
19(1)(f) 0
20 0
21 0
22(1)(a)(i) 0
22(1)(a)(ii) 0
22(1)(a)(iii) 0
22(1)(b) 0
22(1)(c) 0
22(2) 0
22.1 0
22.2 0
22.3 0
22.4 0
23(a) 0
23(b) 0
24(a) 0
24(b) 0
25 0
26 0
27 0
27.1 0
28 0

3.3 Exclusions

Exclusions
Section Number of Requests
69(1)(a) 0
69(1)(b) 0
69.1 0
70(1) 0
70(1)(a) 0
70(1)(b) 0
70(1)(c) 0
70(1)(d) 0
70(1)(e) 0
70(1)(f) 0
70.1 0

3.4 Format of information released

Format of information released
Paper Electronic Other
E-record Data set Video Audio
0 14 0 0 0 0

3.5 Complexity

3.5.1 Relevant pages processed and disclosed for paper and e-record formats

Relevant pages processed and disclosed
Number of Pages Processed Number of Pages Disclosed Number of Requests
1744 1416 50

3.5.2 Relevant pages processed by request disposition for paper and e-record formats by size of requests

Relevant pages processed and disclosed by size of requests
Disposition Less Than 100 Pages Processed 101-500 Pages Processed 501-1000 Pages Processed 1001-5000 Pages Processed More Than 5000 Pages Processed
Number of Requests Pages Processed Number of Requests Pages Processed Number of Requests Pages Processed Number of Requests Pages Processed Number of Requests Pages Processed
All disclosed 9 76 0 0 0 0 0 0 0 0
Disclosed in part 4 65 0 0 0 0 0 1603 0 0
All exempted 0 0 0 0 0 0 0 0 0 0
All excluded 0 0 0 0 0 0 0 0 0 0
Request abandoned 36 0 0 0 0 0 0 0 0 0
Neither confirmed nor denied 0 0 0 0 0 0 0 0 0 0
Total 49 141 0 0 0 0 1 1603 0 0

3.5.3 Relevant minutes processed and disclosed for audio formats

Relevant minutes processed and disclosed for audio formats
Number of Minutes Processed Number of Minutes Disclosed Number of Requests
0 0 0

3.5.4 Relevant minutes processed per request disposition for audio formats by size of requests

Relevant minutes processed per request disposition for audio formats by size of requests
Disposition Less than 60 Minutes processed 60-120 Minutes processed More than 120 Minutes processed
Number of requests Minutes Processed Number of requests Minutes Processed Number of requests Minutes Processed
All disclosed 0 0 0 0 0 0
Disclosed in part 0 0 0 0 0 0
All exempted 0 0 0 0 0 0
All excluded 0 0 0 0 0 0
Request abandoned 0 0 0 0 0 0
Neither confirmed nor denied 0 0 0 0 0 0
Total 0 0 0 0 0 0

3.5.5 Relevant minutes processed and disclosed for video formats

Relevant minutes processed and disclosed for video formats
Number of Minutes Processed Number of Minutes Disclosed Number of Requests
0 0 0

3.5.6 Relevant minutes processed per request disposition for video formats by size of requests

Relevant minutes processed per request disposition for audio formats by size of requests
Disposition Less than 60 Minutes processed 60-120 Minutes processed More than 120 Minutes processed
Number of requests Minutes Processed Number of requests Minutes Processed Number of requests Minutes Processed
All disclosed 0 0 0 0 0 0
Disclosed in part 0 0 0 0 0 0
All exempted 0 0 0 0 0 0
All excluded 0 0 0 0 0 0
Request abandoned 0 0 0 0 0 0
Neither confirmed nor denied 0 0 0 0 0 0
Total 0 0 0 0 0 0

3.5.7 Other complexities

Other complexities
Disposition Consultation Required Legal Advice Sought Interwoven Information Other Total
All disclosed 0 0 0 0 0
Disclosed in part 0 0 0 0 0
All exempted 0 0 0 0 0
All excluded 0 0 0 0 0
Request abandoned 0 0 0 0 0
Neither confirmed nor denied 0 0 0 0 0
Total 0 0 0 0 0

3.6 Closed requests

3.6.1 Number of requests closed within legislated timelines

Number of requests closed within legislated timelines
Number of requests closed within legislated timelines 35
Percentage of requests closed within legislated timelines (%) 53.84615385

3.7 Deemed refusals

3.7.1 Reasons for not meeting legislated timelines

Reasons for not meeting legislated timelines
Number of requests closed past the legislated timelines Principal Reason
Interference with operations / Workload External Consultation Internal Consultation Other
30 30 0 0 0

3.7.2 Request closed beyond legislated timelines (including any extension taken)

Number of requests closed within legislated timelines
Number of days past legislated timelines Number of requests past legislated timeline where no extension was taken Number of requests past legislated timeline where an extension was taken Total
1 to 15 days 6 0 6
16 to 30 days 2 0 2
31 to 60 days 3 0 3
61 to 120 days 3 0 3
121 to 180 days 5 0 5
181 to 365 days 6 0 6
More than 365 days 5 0 5
Total 30 0 30

3.8 Requests for translation

Number of requests closed within legislated timelines
Translation Requests Accepted Refused Total
English to French  0 0 0
French to English  0 0 0
Total 0 0 0

Section 4: Disclosures Under Subsections 8(2) and 8(5)

Number of requests closed within legislated timelines
Paragraph 8(2)(e) Paragraph 8(2)(m) Subsection 8(5) Total
0 0 0 0

Section 5: Requests for Correction of Personal Information and Notations

Number of requests closed within legislated timelines
Disposition for Correction Requests Received Number
Notations attached 0
Requests for correction accepted 0
Total 0

Section 6: Extensions

6.1 Reasons for extensions

Reasons for extensions
Number of requests where an extension was taken 15(a)(i) Interference with operations 15 (a)(ii) Consultation  15(b)
Translation purposes or conversion
Further review required to determine exemptions Large volume of pages Large volume of requests Documents are difficult to obtain Cabinet ConfidenceSection (Section 70) External Internal
0 0 0 0 0 0 0 0 0

6.2 Length of extensions

Reasons for extensions
Number of requests where an extension was taken 15(a)(i) Interference with operations 15 (a)(ii) Consultation  15(b)
Translation purposes or conversion
Further review required to determine exemptions Large volume of pages Large volume of requests Documents are difficult to obtain Cabinet ConfidenceSection (Section 70) External Internal
1 to 15 days 0 0 0 0 0 0 0 0
16 to 30 days 0 0 0 0 0 0 0 0
31 days or greater  0 0 0 0 0 0 0 0
Total 0 0 0 0 0 0 0 0

Section 7: Consultations Received From Other Institutions and Organizations

7.1 Consultations received from other Government of Canada institutions and other organizations

Other complexities
Consultations Other Government of Canada Institutions Number of Pages to Review Other Organizations Number of Pages to Review
Received during the reporting period 0 0 0 0
Outstanding from the previous reporting period 0 0 0 0
Total 0 0 0 0
Closed during the reporting period 0 0 0 0
Carried over within negotiated timelines 0 0 0 0
Carried over beyond negotiated timelines 0 0 0 0

7.2 Recommendations and completion time for consultations received from other Government of Canada institutions

Recommendations and completion time for consultations received from other Government of Canada institutions
Recommendation Number of days required to complete consultation requests
1 to 15 Days 16 to 30 Days 31 to 60 Days 61 to 120 Days 121 to 180 Days 181 to 365 Days More Than 365 Days Total
Disclose entirely 0 0 0 0 0 0 0 0
Disclose in part 0 0 0 0 0 0 0 0
Exempt entirely 0 0 0 0 0 0 0 0
Exclude entirely 0 0 0 0 0 0 0 0
Consult other institution 0 0 0 0 0 0 0 0
Other 0 0 0 0 0 0 0 0
Total 0 0 0 0 0 0 0 0

7.3 Recommendations and completion time for consultations received from other organizations outside the Government of Canada

Recommendations and completion time for consultations received from other organizations outside the Government of Canada
Recommendation Number of days required to complete consultation requests
1 to 15 Days 16 to 30 Days 31 to 60 Days 61 to 120 Days 121 to 180 Days 181 to 365 Days More Than 365 Days Total
Disclose entirely 0 0 0 0 0 0 0 0
Disclose in part 0 0 0 0 0 0 0 0
Exempt entirely 0 0 0 0 0 0 0 0
Exclude entirely 0 0 0 0 0 0 0 0
Consult other institution 0 0 0 0 0 0 0 0
Other 0 0 0 0 0 0 0 0
Total 0 0 0 0 0 0 0 0

Section 8: Completion Time of Consultations on Cabinet Confidences

8.1 Requests with Legal Services

Requests with Legal Services
Number of Days Fewer Than 100 Pages Processed 101-500 Pages Processed 501-1000 Pages Processed 1001-5000 Pages Processed More Than 5000 Pages Processed
Number of Requests Pages Disclosed Number of Requests Pages Disclosed Number of Requests Pages Disclosed Number of Requests Pages Disclosed Number of Requests Pages Disclosed
1 to 15 0 0 0 0 0 0 0 0 0 0
16 to 30 0 0 0 0 0 0 0 0 0 0
31 to 60 0 0 0 0 0 0 0 0 0 0
61 to 120 0 0 0 0 0 0 0 0 0 0
121 to 180 0 0 0 0 0 0 0 0 0 0
181 to 365 0 0 0 0 0 0 0 0 0 0
More than 365 0 0 0 0 0 0 0 0 0 0
Total 0 0 0 0 0 0 0 0 0 0

8.2 Requests with Privy Council Office

Requests with Privy Council Office
Relevant pages processed and disclosed by size of requests Fewer Than 100 Pages Processed 101-500 Pages Processed 501-1000 Pages Processed 1001-5000 Pages Processed More Than 5000 Pages Processed
Number of Requests Pages Disclosed Number of Requests Pages Disclosed Number of Requests Pages Disclosed Number of Requests Pages Disclosed Number of Requests Pages Disclosed
1 to 15 0 0 0 0 0 0 0 0 0 0
16 to 30 0 0 0 0 0 0 0 0 0 0
31 to 60 0 0 0 0 0 0 0 0 0 0
61 to 120 0 0 0 0 0 0 0 0 0 0
121 to 180 0 0 0 0 0 0 0 0 0 0
181 to 365 0 0 0 0 0 0 0 0 0 0
More than 365 0 0 0 0 0 0 0 0 0 0
Total 0 0 0 0 0 0 0 0 0 0

Section 9: Complaints and Investigations Notices Received

Complaints and Investigations Notices Received
Section 31 Section 33 Section 35 Court action Total
0 0 0 0 0

Section 10: Privacy Impact Assessments (PIAs) and Personal Information Banks (PIBs)

10.1 Privacy Impact Assessments

Privacy Impact Assessments
Number of PIAs completed 16
Number of PIAs modified 0

10.2 Institution-specific and Central Personal Information Banks

Complaints and Investigations Notices Received
Personal Information Banks Active Created Terminated Modified
Institution-specific 54 0 0 0
Central 0 0 0 0
Total 54 0 0 0

Section 11: Privacy Breaches

11.1 Material Privacy Breaches reported

Material Privacy Breaches reported
Number of material privacy breaches reported to TBS 3
Number of material privacy breaches reported to OPC 3

11.2 Non-Material Privacy Breaches

Non-Material Privacy Breaches
Number of non-material privacy breaches 15

Section 12: Resources Related to the Privacy Act

12.1 Allocated Costs

Non-Material Privacy Breaches
Expenditures Amount
Salaries $79,421
Overtime $0
Goods and Services $0
Professional services contracts $0  
Other $0
Total $79,421

12.2 Human Resources

Human Resources
Resources Person Years Dedicated to Privacy Activities
Full-time employees 1.135
Part-time and casual employees 0.000
Regional staff 0.000
Consultants and agency personnel 0.000
Students 0.000
Total 1.135
Note: Enter values to three decimal places.

Appendix C: Microdata linkages 2021-2022

Approved record linkages containing personal information

Canadian Forces Cancer and Mortality Study II (CF CAMS II) and the Veteran Suicide Mortality Study (VSMS) (005-2021)

Purpose: Canadian Forces (CF) are tasked with protecting Canada and its citizens from threats to security. CF members may be involved in combat, peace-keeping and observer missions, post-conflict peace building and humanitarian assistance. The very nature of these operations can pose unusual and uncommon exposures with known and unknown risks. Adverse outcomes, including death, may be immediate or delayed. In order to identify risks, Department of National Defence (DND) and Veterans Affairs Canada (VAC) must be able to conduct on-going analysis and interpretation of health information for CF personnel during and after their active military service period.

DND and VAC do not currently have access to complete information on mortality and cancer outcomes of serving and retired CF personnel.

The Canadian Forces Cancer and Mortality Study II, and the Veteran Suicide Mortality Study address major gaps in the health surveillance of CF personnel (serving and released). The general objectives of the studies are to describe the mortality and cancer experience in order to inform:

  • Health promotion and health protection policies and programs for serving personnel
  • Programs that deliver care for veterans (released), and their families.

Output: Only aggregate tabular statistics that conform to the confidentiality provisions of the Statistics Act and any applicable requirements of the Privacy Act will be released outside of Statistics Canada.

Findings from the Canadian Forces Cancer and Mortality Study, and the Veterans Suicide Mortality Study will be disseminated through DND and VAC publications, in peer-reviewed journals, through Veterans Associations publications and in scientific meetings/conferences. All information and reports will contain non-confidential aggregate statistics that will not result in the identification of individual members. If required, additional presentations of study results will be provided by the Canadian Forces Health Services Group at DND to CF leadership and employees; and by VAC's Research Directorate to the Department of Veterans Affairs' leadership and employees.

Record linkages for the 2021 Census of Population (007-2021)

Purpose: The purpose of this linkage project is to obtain specific detailed information to supplement or replace the data collected through the 2021 Census questionnaires and to improve overall the data quality of the Census Program. This use of record linkage provides better-quality, detailed information for small communities and populations, saves time and money, and ensures that the census remains accurate, relevant and efficient. By expanding the use of administrative data in the 2021 Census through record linkage, the burden of response is also reduced as Canadians are spared from supplying the same information they have already provided elsewhere.

Output: The data from these linkages are integrated with collected census data and used to produce estimates for dissemination as part of the standard census product line. Outputs for the census include a wide range of analysis and standard data tables, as well as custom tabulations. Only aggregate statistical estimates and analyses conforming to the confidentiality provisions of the Statistics Act and any applicable requirements of the Privacy Act are released outside of Statistics Canada.

Linkage of emergency and recovery programs and other administrative files with individual and family characteristics from the 2016 Census and selected household surveys (008-2021)

Purpose: This linkage project will help to measure the extent of income support provided during the pandemic. This project will benefit all Canadians on various levels.

Canadians will be better informed to discuss the context surrounding the measures. Furthermore, it will inform discussions about diversity and equity. In addition, it will provide relevant information to the academic community and policy-makers to better serve Canadians.

It will be possible to obtain the level of participation in the programs compared with all workers in the previous year. The integration of selected sociocultural characteristics, level of education and labour market activities that are not available in the administrative databases will enable the analysis to focus on vulnerable or discriminated populations as well as persons with a disability.

Output: To ensure compliance with the provisions of the Statistics Act and the Privacy Act, any data that will be published outside Statistics Canada and its network of Research Data Centres will first be assessed against pre-established confidentiality rules and will be censored to comply with these suppression criteria.

Once these statistical products are certified as compliant with the suppression rules, they will be verified with partner agencies and, where appropriate, published on the Statistics Canada's website.

The products will include a series of characteristic tables in spring 2021. Written analyses will follow.

Ontario Social Assistance Data Linkage Project (009-2021)

Purpose: The Ontario Ministry of Children, Community and Social Services has elaborated a research plan focusing on a better understanding of the characteristics of social assistance recipients, the recipients' interactions with the social assistance and income security systems and the impact of social assistance across a range of recipient outcomes. The project focuses in particular on the earnings, income, and health trajectories of social assistance recipients and their dependents before, during, and after their time in Ontario's caseload. As part of this project, a linkage between the Ontario Social Assistance Member Information File to multiple administrative sources held by Statistics Canada will be performed. The development of analytical research projects are also expected to help researchers, the general public and government to understand and to improve assistance policies or programs.

Output: The analysis file, once identifiers are removed, and the linkage keys will be placed in the Research Data Centre (RDC) network where deemed employees will be able to conduct specific analyses.

All access to the linked microdata file will be restricted to Statistics Canada personnel (including Statistics Canada deemed employees) whose work activities require access. Research reports and presentations to various groups will be generated from the analysis files. Only non-confidential aggregate data or tables conforming to the confidentiality provisions of the Statistics Act and any applicable requirements of the Privacy Act will be released outside of Statistics Canada.

The impact of preterm birth on socioeconomic and educational outcomes of children and families (010-2021)

Purpose: To account for the complex nature of the data and outcomes, we will employ longitudinal methods, multistate models and parametric survival models. We will answer the following questions:

  1. What is the impact of preterm birth on short-term outcomes such as family income, maternal labor market participation, and maternal educational attainment?
  2. What is the impact of preterm birth on long-term outcomes such as the preterm-birth survivor's educational attainment and income?

Output: Only aggregate data that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. Analytical datasets will be placed in the Research Data Centres (RDCs) and access will be granted following the standard RDC approval process. The source datasets will be anonymized and will respect variable restrictions in effect for the source datasets (e.g., hospital, vital statistics, and tax files). Major findings will be used to create research papers for publication in peer-reviewed journals and presentations at workshops and conferences.

Linkage of the 2017 Canadian Survey on Disability (CSD) to select T1FF data and Disability Tax Certificate (DTC) holders. (011-2021)

Purpose: The federal personal income tax system recognizes the additional costs borne by persons with disabilities and provides tax relief to this population through several tax expenditures (e.g., the Disability Tax Credit (DTC)). However, due to the specific eligibility criteria of these measures, using them as proxies for identifying persons with disabilities in tax data may underestimate this population in Canada. On the other hand, while the Canadian Survey on Disability (CSD) may allow a better identification of persons with disabilities, it contains few details on the disability benefit programs such as the DTC. Using these two data sources separately limits the ability to study the impacts of federal income tax expenditures on persons with disabilities.

Output: Results from this data linkage will inform around the current economic context for persons with disabilities in Canada and be instrumental in the development of the Government of Canada's Disability Inclusion Action Plan.

Addition of the Diversity and Skills Database (DSD) to the Linkable File Environment (LFE) of Statistics Canada (012-2021)

Purpose: The purpose of the project is to better understand the ownership and employee characteristics of Canadian enterprises, particularly those supported by the federal government. In the initial usage of this linkage, to be conducted by Statistics Canada's Economic Analysis Division in conjunction with the Treasury Board Secretariat (TBS) of Canada at Statistics Canada's Business Data Access Centre, ownership and employee characteristics of government-supported enterprises in the Business Innovation and Growth Support (BIGS) program will be analysed. This will allow TBS and federal policy makers to determine if the demographic distribution of federal business funding is equitable, reasonable and fair, and how it should be adjusted to maximize the common good of all sectors of Canadian society.

Output: Only non-confidential aggregate statistical outputs and analysis that conform to the confidentiality provisions of the Statistics Act will be released outside Statistics Canada.

These outputs will include aggregate statistical tabulations showing diversity and skills characteristics of owners and employees of enterprises in government support programs such as those included in the Business Innovation and Growth Support program conducted by Statistics Canada on behalf of TBS. The characteristics currently in the DSD are gender, age, immigration status, and business experience.

Military Veteran Status File (013-2021)

Purpose: The purpose of this project is to establish, for the first time, a longitudinal status file that captures all Veterans who have served in the Canadian Armed Forces. This information will be used to expand the research and analysis on the socio-economic status of the entire Veteran population and their families.

Output: Only non-confidential data and analytical products, conforming to the confidentiality provisions of the Statistics Act and any applicable requirements of the Privacy Act will be released outside of Statistics Canada.

Integration of parent and child records from the National Longitudinal Survey of Children and Youth (NLSCY) to data from the T1 Family File (T1FF). (014-2021)

Purpose: The purpose of this project is to answer numerous questions related to parents and children and their outcomes over time, including those that require a long period of observation. These answers can help to improve government program design (for example, parental leave programs) and identify where intervention or solutions could be beneficial (for example, in relation to acceptable levels of air pollution). The NLSCY is Canada's best source of information on children. Linking the NLSCY to the T1FF information of the children and youth and their parents will make it possible to better understand what helps and does not help children over the life course which can benefit the society. Children that are born now will not enter the labour market for another 15 to 30 years, while those of the NLSCY are entering the labour market as we speak.

Output: Dissemination plans may include research papers, data tables, workshops or conferences, media (various forms). Only non-confidential statistical aggregates will be disseminated outside of Statistics Canada.

Alberta Interprovincial Talent Mobility (015-2021)

Purpose: The Alberta Interprovincial Talent Mobility project objective is to understand the current landscape of talent supply and retention in Alberta. In particular, the project will help quantify the talent exodus, if any, from Alberta and help inform interventions that are targeted towards retaining talented high school graduates in the Alberta post-secondary education system and the labour force. It will also inform the adequacy of current post-secondary education programming available to Albertans.

Output: The linked outcome file, with all identifiers removed, will be made available to the Alberta Ministry of Advanced Education in the Statistics Canada, Alberta Secure room, located in the Alberta Office of Statistics and information (OSI).

Linkage of APEX-AMI clinical cohort to hospitalization and socioeconomic data (016-2021)

Purpose: The purpose of this project is to create a series of outcome files resulting from the APEX-AMI files being linked to DAD, CVSD, and T1FF data.

The specific aims of this project are to study the:

  • Differences in characteristics of patients from Canada enrolled in a clinical trial known as the Assessment of Pexelizumab in Acute Myocardial Infarction (APEX AMI) and not enrolled in the trial during the same time period (e.g. age, sex, urban/rural residence, marital status, socio-economic status (SES));
  • Differences in health care resource (e.g. number of hospitalizations, days in hospital, cardiovascular procedures) and long-term mortality among patients enrolled in the trial compared to those not enrolled in the trial;
  • Impact of marital status on long-term mortality in patients with a ST-Elevation Myocardial Infarction (STEMI); and
  • Impact of SES on long-term mortality in patients with a STEMI.

The integrated dataset will fill an existing data gap by examining enrollment in clinical trials through an equity, diversity, and inclusiveness (EDI) lens. For example, if we find the ratio of men to women enrolled in the trial is significantly different from the proportion of men to women who could have been enrolled in the trial, it would inform the design and conduct of future clinical trials. The integrated data will also be able to shed light on the long-term health outcomes of patients enrolled in the trial and compare them to those who were not enrolled in the trial. The linkage will allow for the examination of how social determinants of health (such as urban/rural residence, marital status, and socio-economic status) which were not captured as part of the trial, affect long-term outcomes in patients hospitalized with a STEMI.

Output: Only aggregate data that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. Analytical datasets will be placed in the Research Data Centres (RDCs) and access will be granted following the Microdata Access Portal application process. Patient identifiers resulting from the linkage will be removed from the linked datasets and the datasets will respect variable restrictions in effect for the source datasets (e.g. Discharge Abstract Database, Vital Statistics – Death Database, and T1 Family File). All linked datasets that will be produced will have their identifiers removed before they are placed in the RDCs. Major findings will be used to create research papers for publication in peer-reviewed journals and presentations at workshops and conferences.

The Impact of Surgery on Work and Earnings for those with Degenerative Conditions of the Spine, Hip and Knee (017-2021)

Purpose: The specific aim of this project is to study the impact of surgery on employment and earnings for patients with osteoarthritis of the spine, hip and knee.

Our central hypothesis is that surgical intervention for end-stage osteoarthritis of the spine, hip and knee will result in elevated workforce participation and increased earnings. We will evaluate this using linked longitudinal health and earnings data. Healthcare data will be derived from the Canadian Institute for Health Information Discharge Abstract Database (DAD), the National Ambulatory Care Reporting System (NACRS), and the Canadian Community Health Survey (CCHS). Earnings data will be obtained from the T1 Family File, which contains yearly tax returns for all Canadians.

Output: Only aggregate data that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. Analytical datasets will be placed in the Research Data Centres (RDCs) and access will be granted following the standard RDC approval process. The source datasets will be anonymized and will respect variable restrictions in effect for the source datasets (e.g., hospital, vital statistics, and tax files). All linked file(s) that will be produced will have their identifiers removed before they are placed in the RDC. Major findings will be used to create research papers for publication in peer-reviewed journals and presentations at workshops and conferences.

Atlantic Student Tracking System (ASTS) project (019-2021)

Purpose: The objective of the Atlantic Student Tracking System project is to understand the pathways of current and prospective students in the Atlantic provinces, from Kindergarten to Grade 12 through to postsecondary education.

In particular, the project will provide policy-relevant statistical information by identifying the pathways Atlantic K-12 students follow as they enter, move through and complete their postsecondary education as well as to the labour market. The project builds upon what is currently available in the Atlantic provinces by including postsecondary and apprenticeship enrolment of students in all Canadian provinces, so that movement of high school graduates outside the Atlantic provinces can be fully understood. It also allows study of graduate outcomes related to earnings and employment.

Output: The regional linked outcome file, with all identifiers removed, will be made available to the clients in the New Brunswick University Research Data Centre.

Graduate Outcome Indicators, Project (020-2021)

Purpose: The Graduate Outcome Indicators aims to provide policy-relevant statistical aggregates on students and graduates of Alberta's universities and colleges. In particular, the project will focus on the outcomes and pathways of students and graduates. The expected result is that Alberta will have a greater understanding of student pathways, transitions to the labour market and outcomes over time.

Output: The linked outcome file, with all identifiers removed, will be made available to the Alberta Ministry of Advanced Education in the Statistics Canada, Alberta Secure room, located in the Alberta Office of Statistics and information (OSI).

Linkage of the 2020 Canadian Internet Use Survey (CIUS) data to the 2019 T1 Family File, and Longitudinal Immigration database (IMDB) (021-2021)

Purpose: The purpose of the linkage is to respond to the data needs of the Government of Canada to measure the digital economy, including informing the Universal Broadband Fund. As the barriers to accessing digital technologies and their impacts can vary by different socioeconomic and demographic characteristics, it is important to include this perspective when producing statistics where possible in order to inform relevant policies and programs. Income and Immigration statistics are very important when looking at differences in Internet access and use to determine barriers and to address issues specific to the digital divide. These data are not collected in the questionnaire and can only be obtained through microdata linkage.

The CIUS collects information on internet access and use amongst Canadians 15 years of age or older in the 10 provinces. Historically, data on household income and other sociodemographic characteristics have been collected through self-report. Linkage through the SDLE offers the opportunity to link to administrative data sources to reduce respondent burden and increase data quality, following a well-proven method used by many other social surveys.

Variables from the T1FF file and the IMDB database will be linked to the CIUS data to provide a more comprehensive dataset.

Output: Only aggregate data that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. Findings are expected to be used to inform policy, for research papers, internal and external reporting documents, presentations at workshops and conferences, and external publications.

Data will be released in the following products:

  1. Microdata file in the Research Data Centres (RDC)
  2. Public Use Microdata File (PUMF)
  3. Aggregates in client tables

Developing a Socio-Demographic Profile of Recipients of the Wage Earner Protection Program to Support Program Evaluation (023-2021)

Purpose: The main objective of this study is to develop a profile of key socio-demographic characteristics for recipients of the Wage Earner Protection Program (WEPP). The linkage will provide information about income, employment, disability and ethnicity. The socio-demographic profile will be used to evaluate the demographics of individuals benefitting from the Wage Earner Protection Program in order to inform future policy decisions. The evaluation will be presented to ESDC's Performance Measurement and Evaluation Committee in 2022. Based on the analysis of the linked files, observations about the program will be made that could result in changes to how the program operates.

Output: All access to the linked microdata file will be restricted to Statistics Canada personnel (including Statistics Canada deemed employees) whose work activities require access. Only aggregate data that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. The linked outcome files will be made available in Statistics Canada's Research Data Centre. Findings will be used in research papers and in presentations at workshops and conferences. Statistics Canada will also explore opportunities to collaborate with the client, as well as other partners, on data releases on this topic.

Evaluation of Federally-Funded Drug Treatment Courts (2015-2018 Cohort) (024-2021)

Purpose: Drug Treatment Courts (DTCs) are specialized problem-solving courts that provide individuals involved in non-violent crime related to substance use with an alternative to the conventional justice system by offering them the opportunity to complete a judicially-supervised substance use treatment program. The objective of this study is to estimate the extent to which federally funded DTCs are associated with reductions in re-contact with the criminal justice system compared to the conventional criminal justice process. The results will inform future criminal justice policy and program decisions aimed at improving public safety.

Output: Only non-confidential aggregate statistics and analyses that will not result in the identification of an individual person, business or organization will be released outside of Statistics Canada. Findings will be reported in the form of an analytical report, which may be published by the Department of Justice Canada.

A profile of the Canadian quantum sector (028-2021)

Purpose: The goal of this project is to produce the first profile of the quantum computing sector in Canada. This first profile will serve as a baseline to assess the impact of the Government of Canada's National Quantum Strategy.

A list of businesses in the quantum sector in 2021 from Innovation, Science and Economic Development Canada will be linked to the Canadian Employer–Employee Dynamics Database to create a profile of the sector, specifically, on aspects pertaining to the business, such as revenue and employment, and on aspects of the workers, such as gender and age.

Output: Statistics Canada will provide the following output to Innovation, Science and Economic Development Canada:

  1. A methodology report explaining the file matching processes, constraints and key issues related to the quality of the data;
  2. A document containing non-confidential statistics for the quantum sector, such as: the total revenue; sales; net income; average number of years in business; total employment; as well as the number of workers by sex, age, income-level and geography.

Only non-confidential aggregate statistical outputs and analyses that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada.

Improving residence information on Canadian Vital Statistics – Deaths Database (029-2021)

Purpose: The specific near-term aim of this project is to address the gaps in the understanding of COVID-19 mortality related to the characteristics of the decedent's residence and, in particular, better identify deaths occurring to residents of nursing and residential care facilities in the COVID-19 pandemic.

This will be performed by linking the decedent in the Canadian Vital Statistics – Deaths (CVSD) database to the Address Register (AR)/Statistical Building Register (SBgR), Business Register (BR), Canadian Housing Statistics Program (CHSP) data, and Nursing and Residential Care Facilities Survey (NRCFS) through the decedent's address of residence.

The demand for such information is high and the Public Health Agency of Canada (PHAC) and other stakeholders have explicitly communicated this data need to Statistics Canada to help support their responses to the pandemic.

Additionally, in the longer term, the purpose of the linkage is to fill data gaps and improve knowledge related to:

  • The influence of collective or structural characteristics of the dwelling on broader mortality outcomes.
  • The influence of neighbourhood characteristics on mortality outcomes.

Output: -

  • A derived categorical variable that describes, at a high level, the characteristics of the dwelling of the decedent will be added to the master file of the Canadian Vital Statistics – Deaths database.
  • Non-confidential aggregate statistics and analyses that conform to the confidentiality provisions of the Statistics Act intended for release outside of Statistics Canada.
  • Analytical datasets may also be placed in the Research Data Centres (RDCs) and access will be granted following the standard RDC approval process. The source datasets will be anonymized and will respect variable restrictions in effect for the source datasets (e.g., vital statistics).

A Comprehensive Analysis of the Pathways to Education Program on Health and Crime Outcomes of Eligible Participants (033-2021)

Purpose: The study will examine the average outcomes of the Pathways to Education Canada (Pathways) program on its participants. It builds upon the previous studies focusing on the economic and academic outcomes of Pathways, and extends to other non-pecuniary outcomes, such as health and crime. Specifically, it will examine the channels through which Pathways improves the health and mitigates crime outcomes of its participants. This study will contribute to the academic literature on identifying the channels through which comprehensive interventions delivered at the high school level improve outcomes. The findings from the study will be used by ESDC to more accurately evaluate the Pathways program. More generally, they will enable the Department to better design and deliver the program in helping students in disadvantaged communities in Canada. In addition, the project will contribute to building the Department's capacity – as part of the departmental evaluation plan in 2022 – monitoring and evaluating early intervention and social partnership initiatives.

Output: Only non-confidential aggregate statistical outputs and analyses that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. The information will be presented in the form of tables of regression results and summary statistics related to the project's goal of evaluating the Pathways program.

Access to the analytical file by researchers who have become deemed employees of Statistics Canada, will be by following the approved standard procedures for access via Statistics Canada's Federal Research Data Centre or Research Data Centre.

Linkage of the 2020 General Social Survey (cycle 35), T1FF, Emergency and Recovery Benefits (ERB) file, and Longitudinal Immigrant Database (IMDB) (037-2021)

Purpose: This integrated analytical dataset will allow researchers to provide new insights into the impacts of the pandemic on diverse population groups. The linked dataset will be used to examine the role government transfer payments play in reducing inequality and the societal impacts of long-term economic exclusion (e.g., lack of social cohesion).

Output: The integrated data, which will not contain any direct personal identifiers, will be available to deemed employees to use in a Research Data Centre (RDC). Access will be granted following the standard RDC process. All data and analytical products to be released outside of Statistics Canada will conform to the confidentiality provisions of the Statistics Act.

Linkage of the Canadian Correctional Services Survey to the Census of Population and the National Household Survey for Disaggregated Data Evaluation (038-2021)

Purpose: The Canadian Correctional Service Survey (CCSS) collects comprehensive microdata from correctional service programs in Canada, including whether persons supervised self-report as Indigenous or to a racialized group. Over-representation of Indigenous persons and other racialized groups, in particular Black Canadians, is one of the most important issues facing the criminal justice system. To better understand Indigenous and Racialized group information being collected by correctional service programs, and whether or not there may be under-reporting in the correctional data, CCJCSS proposes a record linkage between the CCSS and the Census of Population. The project will identify individuals responding to both the corrections survey and the Census, to compare how consistently Indigenous and racialized group information is being reported overall between the two data collection mechanisms.

Output: Only non-confidential aggregated tables, conforming to the confidentiality provisions of the Statistics Act, will be released outside of Statistics Canada. Confidentiality rules for the Census would be applied to all products before release.

Canadian Perinatal Health Surveillance (001-2022)

Purpose: The report on Canadian maternal and infant health indicators and their determinants, with a focus on the social determinants of health. Specific research questions include, but are not limited to, the following:

  • What are the rates of infant/fetal outcomes such as stillbirth, preterm birth and neonatal mortality for various sociodemographic subgroups (e.g., income quintiles, maternal educational attainment, immigrant status) and by birthweight.
  • What are the rates and causes of death among women who have given birth (live or stillbirth) in the 12 months prior to their death? How do these rates compare to conventional maternal mortality statistics?
  • How do the underlying cause of death in vital statistics compare to the diagnoses and interventions recorded in hospital discharge data for pregnancy-related deaths?
  • What are the underlying cause(s) of death for infants in the neonatal and post-neonatal periods, and how do these compare over time?

Output: Only aggregate data that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. Analytical datasets will be placed in the Research Data Centres (RDCs) and access will be granted following the standard RDC approval process. The source datasets will be anonymized and will respect variable restrictions in effect for the source datasets (e.g., hospital, vital statistics, and tax files). Major findings will be used to create research papers for publication in peer-reviewed journals and presentations at workshops and conferences.

Microdata Linkage for the Canadian Fishing Fleet Cost and Earnings Study (Phase 3) (003-2022)

Purpose: This study is carried out on a cost-recovery basis by Statistics Canada for Fisheries and Oceans Canada. Its purpose is to develop a methodological framework that will allow Fisheries and Oceans Canada to evaluate the financial performance of a subset of fishing fleets across Canada in a more efficient and cost-effective manner and to test it by preparing aggregate-level statistical tables.

Output: Statistical tables will be prepared at the aggregate level while meeting the confidentiality provisions of the Statistics Act. Only statistics such as averages, standard deviations, etc., will be provided to the client. The linkage will be performed at Statistics Canada by Statistics Canada staff, and the linked files will be kept on a secure, password-protected server.

Analysis of the profile of recipients of a Guaranteed Income Supplement (GIS) mail-out and the determinants of their response through record linkage with Census and T1FF data. (004-2022)

Purpose: The main objective of this study is to develop a profile of key socio-demographic characteristics of respondents and non-respondents to the GIS mail-out. The proposed study will link the records of mailing recipient list to their background and survey information from the 2016 Census and income data from the T1 Family File (T1FF). The linkage results will allow us to conduct a comparative analysis of the profiles of the two groups and uncover relevant differences between them. It will also allow us to assess the importance of recipients' personal characteristics and attributes for response to the mail-out and the determinants of response probability.

Output: All access to the linked microdata file will be restricted to Statistics Canada employees (including Statistics Canada deemed employees) whose work activities require access. Only aggregate data that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. The linked outcome files will be made available in Statistics Canada's Research Data Centre, with access limited to authorized analysts from ESDC Chief Data Office. The results of linked data analyses will be used to inform ESDC senior management, relevant program areas and internal stakeholders on the topic, as well as to advise on outreach activities related to the Reaching All Canadians initiative. Key highlights, high-level findings, and aggregate summary statistics of the data may also be shared with the Office of the Auditor General of Canada upon request.

Exploring the Demographic and Socio-Economic Characteristics Associated with Repeated Convictions among Individuals who have been Supervised by a Correctional Program (005-2022)

Purpose: The purpose of this microdata linkage project is to explore the extent and nature of new criminal convictions among individuals who have been supervised by a correctional program. This project will also explore the demographic and socio-economic factors associated with repeated convictions, including employment, education, household composition, health, and use of social services. Previous research has shown that a small group of individuals is responsible for a disproportionate amount of crime, and that these individuals are more likely to be economically marginalized, have higher mortality rates, and be hospitalized more frequently. Therefore, understanding the characteristics associated with repeated convictions is important for criminal justice policy, programs, and initiatives aimed at preventing and reducing crime. Furthermore, the current project will inform the development of integrated, multi-agency interventions to improve socio-economic outcomes for at-risk populations.

Output: Analytical files will be used by Statistics Canada to produce non-confidential aggregate statistical tables and analytical reports, such as reports for Statistics Canada's flagship justice and public safety publication, Juristat. Anonymous justice data will also be placed in Statistics Canada's Research Data Centres, along with key files allowing integration with other Statistics Canada files, to facilitate research on the demographic and socioeconomic factors associated with repeated convictions within a secure research environment. Researchers must become deemed employees of Statistics Canada in order to access the files in the Research Data Centres. Additionally, access will only be granted once a research proposal has been approved.

Microdata linkage for community-level analysis of fishing incomes and communities (006-2022)

Purpose: This study is being carried out on a cost-recovery basis by Statistics Canada for Fisheries and Oceans Canada (DFO). Its purpose is to improve the geographic accuracy of tax files by combining them with census location data at the municipal level to allow DFO to better assess the situation of fishing communities in Canada in order to support policy development and decision making. The outputs will be aggregate-level statistical tables that will allow DFO to evaluate the fishing reliance of communities in British Columbia as a pilot to see if this type of linkage can improve the geographic accuracy of tax data by appending census geographic information.

Output: Statistical tables will be prepared in conjunction with the International Cooperation and Methodology Innovation Centre at the aggregate level while meeting the confidentiality provisions of the Statistics Act. Only aggregate statistics such as counts, percentages and sums will be provided to the client and only after appropriate suppression has been applied. A total of three tables will be provided to the client, one for each tax year of interest, giving information at the community level for all communities in British Columbia for which data can be published. A short report on the methodology and results will also be delivered to the client.