Introduction

The Treasury Board Secretariat (TBS) and Statistics Canada (StatCan) have partnered to administer the Public Service Employee Survey (PSES). Federal public servants will be invited to complete the survey. The PSES will support the development of strategies to meet the needs of public servants and address any issues identified.

Objective

A privacy impact assessment for Public Service Employee Survey (PSES) was conducted to determine if there were any privacy, confidentiality or security issues with this activity and, if so, to make recommendations for their resolution or mitigation.

Description

This voluntary survey is conducted under the authority of the Statistics Act. It is planned that this partnership will continue; with the PSES to be collected every two years, and other data collection activities happening in alternate years. In the past, Statistics Canada conducted the PSES every three years, with no alternate year activities.

The project also includes the acquisition of PSES 2018, 2019 and 2020 data from the Treasury Board Secretariat of Canada (TBS) under the authority of the Statistics Act to ensure all cycles of the PSES are in one data environment. This is essential to supporting the trend analysis needs of PSES data users, researchers and participating departments and agencies.

Risk Area Identification and Categorization

The Risk Area Identification and Categorization remains unchanged from the original.

Conclusion

This assessment of the Public Service Employee Survey did not identify any privacy risks that cannot be managed using existing safeguards.

Table of contents

• Message from the Canadian Statistics Advisory Council
• Recommendation 1
• Recommendation 2
• Recommendation 3
• Recommendation 4
• 1. High-quality data are central to Canada's economic success and well-being
  • 1.1 Misinformation and disinformation undermine trust in quality data
  • 1.2 Leadership is key to the development of data across government
• 2. Canada's societal issues demand greater collaboration and data sharing
• 3. Harness technology and skills to move forward and lead the way and not be left behind
  • 3.1 Performance and security with cloud technology
  • 3.2 Role of artificial intelligence in statistics
  • 3.3 Attracting and retaining data science and modern analytics skills
• 4. Keeping the momentum
• Endnotes

Message from the Canadian Statistics Advisory Council

The world has witnessed profound economic, social and technological change over the last decade, and Canada has been no exception. In such a dynamic environment, it is paramount that the Government of Canada and Statistics Canada keep pace with change.

Good data and statistics are essential to support economic growth and ensure Canada's prosperity and well-being. Poor data lead to bad decisions with costly consequences.

To assure that Canada has trusted data and high-quality statistics, it is important that Statistics Canada continues its modernization efforts to keep pace with technological and methodological change. Their data and statistics need to reflect a rapidly changing economy and evolving society. This requires modern data science that responsibly adopts the latest technologies, analytical skills that draw on multiple sectors, and coordinated and intersectional data. Programs must be funded appropriately to keep pace with social and technological change. In the long run, decisions made with timely good data are more insightful, effective and save costs.

Official statistics produced by Statistics Canada and other data producers in the national statistical system are increasingly called into question through misinformation and disinformation. This puts their authority, legitimacy and critical role in society at risk. Leaders and experts in the public, private, academic and media sectors all have a role to play in ensuring the health of the national statistical system, including calling out the misinformation and disinformation that comes with incorrect or misleading statistics.

Clear leadership and stability are key to a strong statistical system. The Council is grateful to André Loranger, the Acting 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. A timely permanent appointment is essential to ensure long-term leadership and stability as the agency responds to the changing needs of society. We offer particular thanks to Étienne Saint-Pierre, Gaëlle Miollan and Sam Ndayishimye of the Canadian Statistics Advisory Council Secretariat for their advice and assistance. We are also grateful to former Chief Statistician, Anil Arora, who offered invaluable insight and support to the Council.

Signed:

The Canadian Statistics Advisory Council

• Dr. Howard Ramos, Chairperson
• Dr. Anke Kessler
• Annette Hester
• Dr. Benoit Dostie
• Dr. Catherine Beaudry
• David Chaundy
• Jan Kestle
• Dr. Stephen Tapp
• Vinamra Mathur

Recommendation 1:
Foster trust and data literacy

Good data and statistics are essential to support economic growth and to ensuring Canada's prosperity and well-being. Poor data can lead to bad decisions with costly consequences. This is true for everyone, including for individual Canadians, for businesses and for the public sector.

Official statistics produced by Statistics Canada and other data producers in the national statistical system are increasingly called into question through misinformation and disinformation, which puts their authority, legitimacy and critical role in society at risk.

Leaders and experts in the public, private, academic and media sectors all have a role to play in calling out misinformation and disinformation that come with incorrect or misleading statistics and charts, or analyses that misinterpret them.

The Chief Statistician of Canada should

1. foster informed public dialogue about the importance of quality data based on robust methods for effective decision making
2. raise awareness of the principles of official statistics including relevance, impartiality, professional standards and transparency across traditional media and social media
3. promote and enhance Statistics Canada's comprehensive data literacy program to enable Canadians and decision makers to assess and use statistical data more effectively.

The Minister of Innovation, Science and Industry should

4. promote the importance of official statistics produced within the national statistical system, including those produced by Statistics Canada, to support economic growth and ensure Canada's prosperity and well-being.

Recommendation 2:
Lead effective national data strategies

Effective national data strategies start with a common understanding among Canadians and governments of priority issues and data required to inform these priorities. Data needs and cost assessments must be conducted for every stage of proposed projects or programs, from planning and implementation to evaluation of results, as well as identifying lessons learned and best practices. When data are shared across jurisdictions, there is a dramatic increase in the ability to plan and evaluate the benefits of programs.

The Chief Statistician of Canada should continue to

1. provide leadership in identifying data gaps and data-sharing opportunities across jurisdictions
2. establish and lead partnerships for developing and coordinating statistical data flows at the federal level
3. set data and statistical methodology standards nationwide.

The Minister of Innovation, Science and Industry should

4. recognize and support Statistics Canada's leadership role in the development of national statistics and national statistical data standards as part of the 2023-2026 Data Strategy for the Federal Public Service.

Recommendation 3:
Invest in technology and data skills

It is paramount that Statistics Canada continues its modernization efforts to keep pace with technological and methodological change. Their data and statistics need to reflect a fast-paced economy and changing society. This requires modern data science and analytical skills, including data coordination, data interpretation, data visualization, geospatial analysis and computational modeling. These investments not only keep pace with change, but importantly increase efficiency and save costs in the long run. This, in turn, better meets Canada's data needs.

The Chief Statistician of Canada should continue to

1. invest in training Statistics Canada staff and in internships to foster data science skills for developing and using new methods and data sources.

The Minister of Innovation, Science and Industry should

2. support the federal government's 2023–2026 Data Strategy for the Federal Public Service with a whole-of-government approach to technology including cloud computing, modern data methods and responsible use of artificial intelligence
3. support ongoing investments in Statistics Canada's cloud infrastructure platform to ensure that its statistical programs effectively meet the needs and expectations of Canadians
4. support a whole of government approach to the hiring and retention of people with specialized data skills. This includes drawing from the many Canadian universities and colleges that offer programs specializing in data science, big data, artificial intelligence and machine learning.

Recommendation 4:
Effectively use artificial intelligence

The federal government is investing billions of dollars to leverage artificial intelligence to support and increase Canadian productivity through enhanced computing capabilities and technological infrastructure. For Statistics Canada, artificial intelligence is not new. The agency has been using linguistic models since the early 1990s in support of coding activities.

The decision to use machine learning and other forms of artificial intelligence for statistical purposes must consider the benefits and risks associated with security, data quality and efficiency. Not all technologies are suitable for producing statistics, and methodology should never be trumped by technology.

The Chief Statistician of Canada should

1. continue to explore new artificial intelligence technologies to improve the production of quality data in areas such as data imaging, data visualization and basic tabular analysis
2. engage with Canadians about the role of artificial intelligence in statistical organizations and the safeguards that have been, and need to be, put in place.

The Minister of Innovation, Science and Industry should

3. recognize and support Statistics Canada's statistical leadership in helping the Government of Canada develop its artificial intelligence strategy.

1. High quality data are central to Canada's economic success and well-being

As the world is changing rapidly and societal problems become more complicated, governments and businesses need crosscutting information that better integrates economic, social, cultural and environmental perspectives and that speaks to Canada's diverse communities. Understanding the interrelationships between societal issues leads to more effective solutions that ensure a vibrant economy and a healthy population.

High-quality data and analyses play an important role in public debate helping government policy makers address pressing problems such as economic growth, the high costs of living, access to affordable housing and social inclusion. Canada's economic growth has slowed down over recent years with a sharp downturn during the pandemic. More disconcerting is the declines in gross domestic product (GDP) per capita since the pandemic that represent a departure from the long-term trend in per capita growth. Much public debate has also emerged over the interrelationships between high levels of temporary migration, housing and the economy. Canadians and policy makers must also be better able to anticipate and respond to the impacts of climate change and devastating environmental events, such as wildfires and flooding.

Canada's weak productivity performance has sparked much concern because, historically, much of the long-term growth in GDP per capita has reflected sustained improvements in labour productivity. Recent studies^{Endnote 1Endnote 2Endnote 3Endnote 4} highlight the negative implications of weaker GDP per capita for living standards and wage growth.

Economic, socio-demographic and environmental concerns are not new, but have become more complex in a technologically fast-changing and global society. Analysts need real-time and granular local data to better understand the factors impacting these issues and determine which Canadians are most affected.

High-quality data are essential for developing and implementing effective policies that support businesses and innovation, which drive economic growth. Public and private sector policies must be grounded on a strong national statistical system that Canadians can trust. This system can only be maintained if Statistics Canada and the federal government keep pace with new technologies and methods. They need to move forward and lead the way and not be left behind.

1.1 Misinformation and disinformation undermine trust in quality data

Quality statistical information is one of Canada's most valuable resources. However, it cannot be taken for granted. Good data and statistics in areas such as productivity, inflation, housing and the environment are essential to support economic growth and ensure Canada's prosperity and well-being. Poor data can lead to bad decisions with costly consequences. This is true for individual Canadians, for businesses and for the public sector.

Official statistics produced by Statistics Canada are increasingly challenged by misinformation with little consideration of the United Nations Fundamental Principles of Official Statistics that include relevance, impartiality, professional standards and transparency. Criticism of the agency and its data in social media and newsfeeds increasingly draws on unsubstantiated sources using methods that are poorly conceived.

Even more disconcerting are inaccurate statements and allegations in the media about Statistics Canada and its data, which, if unopposed, will lead to an erosion of trust in the agency and its leadership. Recent examples include criticisms of the methods used by Statistics Canada to determine the price of consumer goods^{Endnote 5} and the estimates of the number of temporary migrants in Canada^{Endnote 6}. In both cases, the ensuing debates suggest methodological flaws in these challenges to the agency's methods and statistics.^{Endnote 7Endnote 8}

In some cases, these criticisms involve misinformation, where Statistics Canada's data and statistical methods are questioned in good faith. This requires proactive strategies by the agency to respond and correct the record.

More troubling are cases of disinformation, involving deliberate attempts to mislead. Organized disinformation, when it involves official statistics, can undermine confidence in evidence-based decision making and is a real threat to Canadian democracy over time.

Fostering trust and countering misinformation and disinformation

Misinformation and disinformation are best countered through public dialogue that distinguishes good data from poor or misleading data, and which emphasizes how good data supports community well-being. This message cannot come from Statistics Canada alone.

Statistical experts and opinion leaders in the public, private and academic sectors, as well as the media, have a role to play in calling out the misinformation and disinformation. They can raise awareness about the critical role of official statistics in a democracy and attest to how these statistics are based on high standards of impartiality, data quality, robust scientific methods and transparency.

Statistics Canada has a central role to play in helping Canadians find their way through the plethora of competing and conflicting statistics from social networks and traditional media. The agency needs to adapt the way it publishes social and economic indicators in ways that new and younger audiences can relate to and trust. The agency must ensure quality statistical information on current topics is readily available to prevent misinformation from taking hold. The agency must also be proactive and transparent with Canadians about changes to statistical programs and methods, and indicate how they are subject to external methodological review. Within the public service, the federal government has published Countering Disinformation: A Guidebook for Public Servants on its portal on democratic institutions. The guidebook offers a pathway for engaging these challenges.

Experts within the agency should also continue to be proactive in countering misinformation through dialogue with publishers and media who put out erroneous or misleading statistics and charts, or analyses that misinterpret them. Collaborating with sources that have erred in good faith ensures a more effective and credible dissemination of accurate information and official statistics in the long run.

The motives behind disinformation are devious and more difficult to counter. The actions are often meant to undermine trust in democratic institutions. Simply countering with factual official statistics is not sufficient because these are readily rebuffed by the proponents of disinformation. Statistical information that does not abide by professional statistical standards should be publicly dismissed.

Fostering data literacy

Data literacy is key to recognizing and appreciating high-quality and impartial data. The agency needs to do even more outreach with its Data Literacy Training Initiative. This comprehensive program is tailored to different levels of expertise within government departments and the broader public. The program also provides insight on the importance of data relevance, impartiality, professional standards, confidentiality and transparency.

The agency is already very active with schools, providing teachers with educational resources which showcase the use of analytical and data visualization tools to explore topics such as population, housing, food and transportation. These tools provide a basis for the younger generation to build essential skills for the workplace and to appreciate the value of data as they progress through life.

In universities and colleges, more detailed and complex data sets are being made available to students through public use files and Research Data Centres. When instructors use these data, students can learn to discern the quality of data and analyses using more advanced statistical methods. While instructors and students also have access to Statistics Canada's data literacy training program that is publicly available on the agency's website, it is underused by the academic sector. There should be more partnerships between Statistics Canada and academia to co-develop a curriculum that keeps pace with the changing data science and analytical skills needed within the agency and government. Statistics Canada is currently working with the Canadian Research Data Centre Network to determine how data training may be useful in areas such as disaggregated data analysis.

In the Canadian Statistics Advisory Council's 2023 Annual Report, the Council felt that, given the important role of data in federal programs, the data and analysis training offered to federal program managers and analysts should be mandatory. The data literacy training program should also be made available to influencers, journalists, publishers and owners of both social and traditional media.

1.2 Leadership is key to the development of data across government

Statistics Canada has a key leadership role in creating environments where various data sources can effectively and securely be collected and integrated for statistical analysis. The agency is well placed to set national standards for statistical concepts, definitions and classifications, given its internationally recognized expertise in statistical methods and data standards.

The federal government's 2023–2026 Data Strategy for the Federal Public Service addresses many challenges that the Council has highlighted over the past several years. These include the need for a whole-of-government approach to program design and data stewardship for management of statistical data and data standards; embedding and appropriately resourcing data needs up front and throughout the development, delivery, monitoring and evaluation phases; and improving data literacy and digital skills across government.

These federal initiatives are ambitious and will take time to implement. They will also require adequate resources and new funding models. It will be important for Statistics Canada to play a leadership role, considering its expertise in statistical methods and in large-scale transformative management. The work is supported by the Disaggregated Data Action Plan, that was created to support Statistics Canada's efforts to continually identify and fill data and knowledge gaps across programs.

Intersectional approaches are needed

Too often, Canadian research on social and economic inequalities is done in silos, missing the cross-cutting issues, or intersectionality,^{Footnote A} needed to truly address the country's most pressing problems.^{Endnote 9Endnote 10}

For example, when studying environmental concerns, it is a challenge to obtain the information needed to understand what lands and which populations and businesses are most vulnerable. When disasters strike, timely data are required to support immediate relief and the longer-term recovery of communities. Accurate assessments of wildfires require not only satellite data to identify where they occur, but also information on the remote and rural communities affected, including First Nations reserves. This includes social and economic profiles, and data on businesses and assets to enable the proper resources can be mobilized to mitigate damages. These data cannot be looked at in isolation. Looking at them jointly requires modernized data infrastructures, data visualization and creative analytical techniques.

Housing affordability and projected housing stock are other areas where there is demand for more intersectional information. It is important to understand the combination of factors that put certain Canadians at risk of being unable to obtain or afford adequate housing. Decisions by policy makers that are based on solid statistics and analyses are much more likely to successfully support Canadians who are most in need. This requires different jurisdictions to work with Canada Mortgage and Housing Corporation and Statistics Canada to expand the national housing database by securely linking individual records from different data sources and jurisdictions. Private sector firms, such as those in the real estate and construction industries also have valuable data holdings that could be leveraged.

Several years ago, Statistics Canada developed innovative uses of existing data through data linkage environments. The Social Data Linkage Environment allows for the integration of existing census, survey and administrative data files in areas such as population demographics, health, justice, education and income. The Business - Linkable File Environment enables analyses such as on the factors for firm productivity, by linking business microdata from administrative and survey sources. The agency has also developed the Education and Labour Market Longitudinal Platform (ELMLP) in collaboration with federal, provincial, territorial and other stakeholders. The ELMLP allows longitudinal integration of administrative data related to education, enabling a greater understanding of student and apprenticeship pathways and transitions to the labour market and outcomes over time. These linkage environments are powerful tools to support the increased opportunities for cross-cutting and longitudinal data analytics.

Fostering data quality and statistical data standards

Statistics Canada needs to promote the importance of quality data and data standards to both data providers and users as it sets national statistical standards. Its Quality Assurance Framework is leading edge and forms the basis for those developed by international organisations such as the United Nations and the Organisation for Economic Co-operation and Development.

In its quality assurance framework, Statistics Canada defines quality or fitness for use of statistical information in terms of six dimensions: relevance, accuracy, timeliness, accessibility, interpretability, and coherence. Some users might appreciate a single quality rating. However, this is not practical, given that an assessment of quality depends on what the user needs the data for, and they may prioritize one of the six dimensions over another. For example, annual federal transfer payments to provinces and territories amounting to billions of dollars require economic and social indicators of the highest accuracy, while during the pandemic, Statistics Canada published more timely flash economic and employment indicators that were not as accurate as its regular monthly estimates.

Footnotes for section 1.2

Footnote A

Intersectionality relates to the combination of factors that results in how groups and individuals face discrimination and privilege. These factors include age, gender identity, sexual orientation, race, ethnicity, religion and disability.

Return to footnote A referrer

2. Canada's societal issues demand greater collaboration and data sharing

An effective national statistical system is built on mutual relations and the sharing of information and expertise. Statistics Canada cannot and should not do it alone. Collaboration is needed across the public and private sectors to share data for public good. This includes partnerships across provinces, territories, municipalities, business sectors, non-profit sectors, academia, and Indigenous organizations and communities.

The potential cost to Canadians for programs based on poor or incomplete data is enormous. Even in fiscally difficult times, it remains cost-effective to modernize statistical and technical infrastructures and promote data flows that are the foundation for understanding and tackling important issues. In a context of restraint, adaptable and creative funding is possible, especially when based on the whole of government approach advocated in the federal Budget 2024.

When data are shared across jurisdictions, the ability to plan and evaluate the benefits of programs increases dramatically. This requires strong governance and data stewardship models that are trusted by Canadians, that ensure their personal data are secure and that effectively produce the quality detailed data that are required.

Effective national data strategies must be grounded in shared statistical and methodological objectives. This starts with a dialogue across sectors and jurisdictions, led by Statistics Canada and other government leaders, to gain a common understanding of pressing societal issues and the data needed to address them. Data needs, data sharing opportunities and costs assessments must be conducted for every stage of proposed projects or programs, from planning and implementation to evaluation of results and post-mortems. Concepts, definitions and representativeness of data should be examined for consistency with national standards. Methodological adjustments ensure that data across jurisdictions are comparable.

Some noteworthy collaboration initiatives:

Multijurisdictional data on drugs and substance abuse

The Canadian Drugs and Substances Strategy is a good example of multiple jurisdictions coming together to address substance use and the overdose crisis in Canada. Federal, provincial, territorial, community and Indigenous organizations collaborate with professional and regulatory bodies and health care providers. Statistics Canada is partnering with Health Canada and the Public Health Agency of Canada to develop a secure, virtual analytical environment with integrated health and socioeconomic data from across jurisdictions and diverse data providers. This initiative aims to fill critical information gaps about risk and protective factors, as well as populations most at risk for harms related to the ongoing drug and overdose crisis.

Provincial and territorial health data

Integrating data at the provincial and territorial levels adds complexity when jurisdictions become siloed, and legislation and policies create barriers to data sharing. A critical lack of integrated national health data and the need for a pan-Canadian Health Data Strategy have been highlighted by an expert advisory panel reporting to the Public Health Agency of Canada.

The Council was encouraged by the 2023 Canada Health Transfer agreements, which included support for improving data flows and developing national indicators on health care and health care workers. Statistics Canada is contributing to the federal, provincial and territorial Shared Health Priorities by developing new data that will enable annual reporting by provinces and territories on key health indicators for both children and adults. These health indicators will be disaggregated as much as possible by age, gender, urban or rural status, and income.

The potential of these data is demonstrated through data hub initiatives created by health research organizations that work with Statistics Canada, and with provincial and territorial health authorities. Linking health, socioeconomic and environmental data across jurisdictions using national standard definitions and data categories helps researchers understand the complex interplay of influences on human health, well-being and development. The Data Access Support Hub of the Health Data Research Network and the Strategy for Patient-Oriented Research of the Canadian Institutes of Health Research are examples of good practices.

Municipalities data hub

The Centre for Municipal and Local Data has been cited in previous reports as a model for successful collaboration with Statistics Canada. It is the result of an ongoing partnership with the Federation of Canadian Municipalities. Additional funding was announced in the 2024 Budget to continue and expand the data hub. This should include working to address important data gaps such as the costs of maintaining and repairing municipal infrastructures, particularly in light of devastating environmental events such as wildfires and flooding.

Municipalities are also increasingly involved in federal data strategies such as the Canadian Drugs and Substances Strategy and the Housing Statistics Portal cited by the Council in this and previous reports.

Businesses data lab

The Business Data Lab has been cited in previous reports as a model for successful collaboration with Statistics Canada. Since 2022, the Canadian Chamber of Commerce has collaborated with Statistics Canada to generate real-time information on business conditions and analytical insights on various topics related to the economy, particularly for small and medium-sized businesses. In the 2024 Budget, the Canadian Chamber of Commerce received funds to continue and expand the data lab. Statistics Canada will continue to provide the required infrastructure to support the work of the Chamber and collaborate with them on joint initiatives.

It is important that Statistics Canada continues to explore partnership opportunities within the private sector. Establishing partnerships with large private sector organizations to share their big data holdings is challenging because of administrative, legal and fiscal factors, which are not expected to improve in the foreseeable future.

At the same time, these data have great potential to shed significant light on several issues. For example, the real estate sector holds real time data on housing that can offer granular insights to fill gaps that would otherwise be missed, satellite data held by private sector companies can offer new information on rural communities, and partnerships between the telecom sector and Statistics Canada that integrate mobility phone data with census tract information can help to better understand commuting patterns and remote work practices.

Non-profit sector engagement

Statistics Canada has introduced a module for non-profit organizations (NGO) in their Canadian Survey of Business Conditions. The agency has benefited from advice from community, business and non-profit organizations. Funding has also been available through the agency's Disaggregated Data Action Plan. The results highlight the profound impact that NGOs have on Canadians' lives as well as the ongoing significance of these organizations as vital players in a diverse society and a dynamic economy.

Recently Statistics Canada has been collaborating with the NGO Maple Leaf Centre for Food Security to analyse the relationship between poverty and food insecurity. Empowering NGOs to do this kind of work is an important outcome of fostering intersectional data. The resulting article, Food insecurity among Canadian families, expands the current body of knowledge on food security, showing that income alone cannot explain food insecurity. The study, which used a variety of Statistics Canada data sources, found that food insecurity stems from the interplay of various factors, including the stability of income, assets and debt, access to family and social supports, and the cost of living.

First Nations Consumer Price Index

Statistics Canada is providing advice and expertise to the First Nations Tax Commission (FNTC),in collaboration with the Bank of Canada and Indigenous Services Canada. They offer capacity-building support to the FNTC as it explores the measurement of price inflation in diverse and often remote Indigenous communities. This research integrates information across data sources and communities to draw initial insights and estimates of inflationary pressures. Part of the First Nations Data Governance Strategy, this initiative fills an important data gap as Reserves are not included in the national Consumer Price Index.

Indigenous-led data strategies are integral to a national data system. The Council in previous reports , has presented how First Nations, Inuit and Métis communities and organizations have been developing capacity, infrastructure and strategic frameworks to support data governance and data collection processes at both national and regional levels. The First Nations Information Governance Centre (FNIGC) and its regional partners play a leadership role in developing and implementing the First Nations Governance Data Strategy. 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. Surveys administered by FNIGC, in coordination with regional partners^{Endnote 12} cover topics such as health, early education, employment and communities. Statistics Canada provides data capacity-building support to many of these initiatives and is improving the visibility of Indigenous Peoples in Canada's national statistics.

3. Harness technology and skills to move forward and lead the way and not be left behind

It is paramount that Statistics Canada continues its modernization efforts to keep pace with rapid technological and methodological change. With new technologies, there are opportunities to access and share untapped data resources that provide needed perspectives to the issues Canadians face.

This cannot not be done without a strong commitment to funding such infrastructure and promoting a whole-of-government approach to technology including cloud computing, modern data methods and use of artificial intelligence.

3.1 Performance and security with cloud technology

Residing within a secure public cloud data centre, the agency's cloud platform stores statistical information and applications for processing as well as Statistics Canada's official data holdings. It has become a backbone for creating cross-cutting and longitudinal data sets to inform and address the country's problems. Leveraging cloud infrastructure, Statistics Canada has also created a collaboration platform that provides opportunities to coordinate information across federal departments and facilitate collaborations with provinces and territories, municipalities, private and academic sectors and Indigenous governments and organizations.

Use of the cloud has huge potential for developing new methodologies and managing increasingly complex data. The cloud infrastructure is replacing an outdated system infrastructure centred on physical data centres. Several legacy statistical applications need modernization to fully leverage the modern cloud infrastructure in support of a new age of big data and powerful data analytics.

As cloud computing becomes more central to Statistics Canada's work, safeguarding personal information remains a top priority. Statistics Canada uses a scaled approach for authorizing access to its microdata holdings based on their sensitivity. The agency has also aligned itself with mandatory safeguards published by the Canadian Centre for Cyber Security, Treasury Board Secretariat and Shared Services Canada.^{Endnote 13}

The cloud infrastructure platform requires ongoing investments if it is to effectively meet the needs and expectations of Canadians in a sustainable way. Developing and using statistical data today comes with significant costs. This not only includes evergreening and optimizing the cloud platform, but also investments to optimize Statistics Canada's systems, applications and data management infrastructure. Because Statistics Canada's microdata holdings are becoming more analytically powerful, there is a requirement for new levels of computing power. All of these costs must be planned and resourced within new models of procurement.

Remote access to microdata

Cloud computing offers enormous potential for allowing authorized researchers remote access to Statistics Canada's microdata holdings from approved office or home workspaces. A greater network of researchers creates opportunities for collaboration and data integration, leading to more in-depth statistical findings. It also broadens the community of experts able to push back on the misinformation and disinformation discussed earlier. In expanding access, the agency should ensure strategic synergies between the different modes of microdata access as presented in its Continuum of Data Access.

The agency has recently been able to provide virtual access for government researchers, and the academics they collaborate with, within the federal government cloud infrastructure. Appropriate governance and safeguards ensure protection of the confidentiality of the microdata in a virtual environment.

Offering this to academic researchers more generally has added complexity. Establishing a sustainable, secure non-government network requires new partnerships, funding and cloud computing approaches. The Canadian Research Data Centre Network and Statistics Canada are working with their university partners to build a virtual research data centre.

There is also a demand from private sector researchers and non-profit think tanks to have access to the agency's microdata holdings for statistical research purposes. Their research is important to support business innovation and productivity in Canada, as well as intersectional research on issues such as housing, immigration and poverty. As Statistics Canada expands remote access to a broader set of users, additional governance and accountability structures are needed to ensure the safeguarding of personal information.

Improving the scope of census data

The Census of Population and the Census of Agriculture are Canada's primary sources of national local-area data that can be compared across the country. To meet the increased demand for more granular and integrated data, the Census of Population has replaced census questions with administrative data on income and immigration. The Census of Agriculture has also used administrative data to replace questions on revenue, expenses and operating arrangements. In 2021, census data on cannabis farms were produced entirely based on administrative data. Statistical models ensure census data consistency and quality.

The agency is currently researching an increased use of administrative data for the Census of Population. Referred to as a combined census, administrative data already provided to other government departments could, under certain conditions, be used for the purpose of enumerating the population. At the same time, alternate data sources are being explored to replace questions on maple taps, labour, operator characteristics and greenhouses in the Census of Agriculture.

Leveraging innovative modelling techniques and robust administrative data linkage methods would lessen the burden of participation for Canadians and contribute to the long-term efficiency and sustainability of the censuses. It would also enable contingency strategies when faced with collection challenges such as natural disasters.

Addressing declining response rates

Statistics Canada's surveys provide important demographic and socioeconomic characteristics and lived experiences that are not available from other data sources including the census. While the census continues to have a very high response rate (98%), the long-term decline in social survey response rates was exacerbated by the pandemic.

The low response rates for voluntary surveys are particularly disconcerting, as collection response rates for the Canadian Social Survey, the Canadian Community Health Survey and the National Travel Survey are all below 50%. Canadians have become much harder to reach. There is also a fatigue from a continuous stream of surveys from both the private and public sectors. Statistical agencies around the world, as well as private research and analytics firms, are facing this challenge.

As downward pressure on survey responses rates is not likely to ease in the future, Statistics Canada must find ways to account for this in its survey designs and preserve the valuable information that only these surveys provide.

For the mandatory Labour Force Survey, the agency is taking advantage of modern technologies and platforms which can be used to better reach Canadians and provide them with options for responding online.

For its voluntary surveys, Statistics Canada is developing leading edge methods that integrate the agency's census, administrative data and web-based statistical data with survey data. The benefits are numerous. Survey output on communities and on vulnerable populations is becoming timelier and more detailed, and there is reduced respondent burden.

In this welcome groundswell of modernization, it is important to ensure that technology is there to support and not drive methodological design.

3.2 Role of artificial intelligence in statistics

Canada is considered a world leader^{Endnote 14} in a technology that is gaining attention globally—the development and use of artificial intelligence.^{Footnote BEndnote 15Endnote 16} According to the International Monetary Fund (IMF)^{Endnote 17} artificial intelligence can increase productivity, boost economic growth, and lift incomes. However, it can also eliminate jobs and widen inequality. Canada ranks high in the IMF's AI Preparedness Index of countries based on their digital infrastructure, human capital, labor policies, innovation, integration and regulation.

At the same time, without sustained investment in this technology, Canada runs the risk of quickly falling behind.^{Endnote 18} In Budget 2024, the federal government announced investments of $2.4 billion to build computing capabilities and technological infrastructure for Canada's world-leading artificial intelligence researchers and to help businesses increase their productivity by leveraging artificial intelligence solutions. The government is holding public consultations^{Endnote 19} this year to seek input on proposed artificial intelligence initiatives.

The decision to use machine learning and other forms of artificial intelligence for statistical purposes must always consider the benefits and risks with regard to security, data quality and efficiencies. Statistical data produced using artificial intelligence is only as good as the information it uses. Not all technologies are suitable for the production of statistics, and methodology should never be trumped by technology.

Improper use of artificial intelligence when collecting data can lead to an erosion of trust and disengagement of citizens. As this touches the heart of Statistics Canada's core values of trust and privacy of information, the agency has been very active in advocating for the proper use of artificial intelligence by government when dealing with data.

Statistics Canada assesses artificial intelligence from two perspectives. The first is ensuring that their economic, social and environmental indices, data and analyses consider the impact of artificial intelligence. The agency has several initiatives underway including measuring the value of data in the System of National Accounts. The second is leveraging the technology in the production of official statistics. For Statistics Canada and other national statistical offices, modelling and artificial intelligence are not new. The agency has been using linguistic models since the early 1990s in support of coding activities as computer algorithms and statistical models perform automatic and interactive coding tasks. This has led to more efficient data processing and an improvement in data quality.

More recently, Statistics Canada is leveraging new technologies and cloud platforms to use machine learning and large language models at various stages of data visualization and data production. They are being used to predict crop yields, perform basic tabular analysis and engage with Canadians through chatbots. The agency does not use artificial intelligence to infer statistical estimates as the technology has not proven to produce quality statistics.

A notable initiative is the Canadian Coroner and Medical Examiner Database. Machine learning is being used to organize data collected from provinces and territories into coherent datasets, as each jurisdiction has its own method for classifying data. This has improved the national data available to analysts to better detect trends in mortality over time and allow medical examiners and coroners to understand growing hazards.

Statistics Canada should continue to help the Government of Canada develop its artificial intelligence strategy. The Agency plays a key role in the AI and Data Governance Standardization Collaborative, an initiative led by the Standards Council of Canada that brings together industry, government, Indigenous organizations, civil society, academic and research bodies, pan-Canadian organizations, and standards development organizations. On the international front, the agency leads big data and data science expert groups that are identifying and addressing common challenges encountered when incorporating machine learning into the production processes of organizations.

The agency should share its expertise with Canadians on the role of artificial intelligence in statistical organisations and the safeguards that have been and need to be put in place. The dialogue with Canadians would enhance trust in the agency and inform future use of artificial intelligence technology.

Footnotes for section 3.2

Footnote B

Artificial intelligence is a technology that enables computers to simulate human intelligence and problem-solving capabilities. The Organisation for Economic Co-operation and Development defines an artificial intelligence system as a machine-based system that infers, from the input it receives, how to generate outputs such as predictions, content, recommendations or decisions that can influence physical or virtual environments.

Return to footnote B referrer

3.3 Attracting and retaining data science and modern analytics skills

Keeping pace with changing technology and statistical methods requires modern data science and analytical skills, including data coordination, data interpretation, data visualization, geospatial analysis and computational modelling.

Statistics Canada needs data scientists, methodologists, economists, sociologists and environmentalists with these skills to gather, analyze and report on large amounts of data. Applying data visualization in the early stages of survey design and development introduces novel concepts and dimensions to the statistical outputs. As the agency uses more unstructured data forms, they are required to develop statistical formulas and computer algorithms that transform unprocessed data into quality statistical information. The agency's subject matter experts must have strong multidisciplinary training that integrates mathematics, statistical concepts, computer science and data visualization to develop statistical measures that best inform societal issues. In addition, machine learning requires more advanced statistical and methodology probability theory, computer algorithms and neural networks.

These skills are in high demand, and it is a challenge for Statistics Canada to keep up with other departments and the private sector in attracting and retaining workers with these competencies. As part of the 2023–2026 Data Strategy for the Federal Public Service, there should be a whole-of-government approach to the hiring and retention of specialized data skills. This includes drawing from the many Canadian universities and colleges who are now offering programs that specialise in data science, big data, artificial intelligence and machine learning. This also means partnering with universities, so their programs keep pace with the agency's specific needs. To be effective, incentives to attract new and experienced specialists could also be considered by Statistics Canada and the public service.

There are too few partnerships and internships between Statistics Canada and the private sector. More could be considered, though this would require additional funding. Disparities in compensation between the public and private sectors may also present challenges.

Successful cutting edge data science tools are user-focused and accessible across different devices and operating systems. Natural Resources Canada's web portal on Canadian minerals and metal statistics is an example of the power of data visualization to introduce and facilitate understanding of a topic. The portal complies with government accessibility standards and is functional across user platforms. Statistics Canada has created interactive dashboards and data hubs such as the International trade monthly interactive dashboard and the Gender Diversity and Inclusion Hub which have improved access to detailed and multi-sourced data. The agency needs to invest more in this direction to improve on the design, usability, interactivity and performance of data products across user platforms, leveraging the power of visualization tools. Government of Canada budget constraints and hiring ceilings are a challenge that hinder these objectives.

4. Keeping the momentum

Over the past few years, the agency has made important investments in cloud technologies, data analytics and remote access to its data holdings. Its methodologists and analysts are expanding their expertise to work with new types of data, such as satellite imagery, web-based data, bio-specimens and water waste.

Continuing this work is not possible without ongoing investments by the federal government and recognition of Statistics Canada's leadership role that are in line with the 2023–2026 Data Strategy for the Federal Public Service.

The importance of data is echoed in the federal Budget 2024 where Statistics Canada data are cited in the analysis of issues Canadians face, including housing, health, food and crime. The budget proposes new monies for continuing the work of Statistics Canada, in partnership with Canada Mortgage and Housing Corporation and with Canadian Chamber of Commerce in creating the data hubs described as best practices in the Council's 2023 Annual Report. There are also funds to support disaggregated statistics to highlight the diverse lived experiences of different groups, including women, Indigenous People and racialized groups.

The incoming Chief Statistician will have the important task of running Statistics Canada and maintaining the agency's momentum on pursuing modernization, partnerships and trusted statistical leadership.

I. Introduction

The main objective of this survey is to obtain detailed revenue and expenditure data on each college and vocational school in Canada. Coupled with what is already available for the university sector, this gathering of data will provide a complete picture of the financial statistics of postsecondary education as well as vocational training in Canada.

The following notes provide the principles, definitions and guidelines necessary for the completion of the data form. Since it is desirable to obtain figures as comparable as possible from one institution to another, each respondent is requested to:

• provide accompanying notes of explanation in the observations and comments section of the submission for figures that do not follow the guidelines;
• provide comments on items which are excluded from the data, such as cases where provinces are making contributions to repay debt on behalf of an institution or material gifts received as donated service along with their estimated market value;
• estimates should be made whenever possible if income and expenditure figures are not readily available in the required format from the financial records of the institution. When estimates are made they should be indicated with an asterisk (*).

II. Submission

The final deadline for the submission is indicated in the covering letter. The completed questionnaire(s) should be returned in the self-addressed envelope provided.

A copy of the institution's Audited Financial Statements is also requested with your submission. If a copy is not available, please advise Statistics Canada as to the date on which they will be forwarded.

III. Coverage

With the exception of private institutions that only offer courses at the trade and vocational level, the survey covers all private and public non-degree granting institutions that offer educational programs at the postsecondary level and/or at the trade and vocational level. For statistical purposes, institutions are classified as follows:

1. Colleges/Institutes/Polytechnics

   Included in this classification are the colleges of applied arts and technology (CAAT's) in Ontario, general and vocational colleges (CEGEP's) in Quebec, institutes of technology and any other institutions providing education in fields such as paramedical technologies, nursing, agriculture, forestry, nautical sciences, etc.. These institutions offer programs at the postsecondary level, and may offer trade-vocational level programs.

2. Vocational Schools

   This classification includes Community Colleges in Saskatchewan and Vocational Centres in Alberta, government training schools, vocational training centres and any other institution offering programs at the trade-vocational level only.

3. Training in hospitals

   Included in this classification are educational centres located in hospitals, which offer educational or training programs, independently of the community college system, in nursing, radiotherapy, radiography, medical technology, etc..

   To ensure full coverage, it is important that each reporting officer indicates on section 2 of the questionnaire the affiliated campuses included in and/or excluded from the submission.

IV. 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.

V. Authorization to Release

In order for Statistics Canada to release the information provided an 'Authorization to release' form must be signed. The form provided authorizes Statistics Canada to release the information in aggregation to the provincial/territorial level only.

VI. Principles of Reporting

1. Accrual Concept

For the purpose of this survey, the revenue and expenditure data should be reported on an accrual basis. That is, all revenues and expenditures should be reflected in the period in which they are considered to have been earned and incurred respectively. For example, major adjustments, such as retroactive salary and their related benefit costs, should be reported on that basis.

2. Total Income and Expenditures

All income and expenditures of the institution are to be reported. In this regard particular attention should be paid to the following:

• when an institution is provincially governed or consists of a branch of a department, all costs related to the operation, maintenance and administration of the institution are to be reported; the actual funds used to finance those expenditures should be shown as a provincial source of funds;
• consultations may be required with the institution's research department to obtain detailed breakdowns of income sources and expenses related to sponsored research;
• capital expenditures, as well as related revenues, that are financed by a government Department or Ministry other than the one responsible for the institution must be included in this report; the reporting officer is responsible for obtaining and providing this information;
• the figures reported should not include income or expenditures for the purpose of creating or eliminating an appropriation; however, any actual income or expenditure transaction recorded directly in reserve accounts should be included in the figures reported; this also applies to other assets and liability accounts; provisions for replacement of assets are considered to be transfers to reserve or appropriation accounts and should not be reported as expenses;
• receipts and expenses relating to special purpose, trust and other funds of the institution should, as well, be included in the report.

3. Ancillary Enterprises

An ancillary enterprise is an entity that exists to furnish goods and services to students, staff or others, and that charges a fee directly related to, although not necessarily equal to, the cost of the goods or services. To reflect properly the full cost of these enterprises, you should report their total gross revenues and total gross expenditures in the appropriate cells in the Schedule 1 and Schedule 2A. In addition, a breakdown by type of ancillary enterprises (bookstores, food services, residences, parking) must be completed on the Supporting Schedule A.

4. Reporting of Income

When reporting the sources of funds in the operating, sponsored research and capital income in Schedule 1, it is important to show the revenues under the headings that correspond to the immediate source of funds for the institution. For example, if an institution offers training courses for which Employment and Social Development Canada (ESDC) purchases seats, then the amount of money paid by ESDC should be shown under "Federal" only if the money is received directly by the institution. If the money is received by a third party (provincial government) and then transferred to the institution, then the direct source of funds is the "Provincial Government".

VII. Definitions

1. Program Cost Groups

This section defines the program cost groups to be used in the reporting of direct instruction expenditures on Schedule 2B of the questionnaire.

The criteria used to define the various program cost groups originates from those used in other surveys conducted by Statistics Canada and also from analysis of different educational systems across Canada. Note that these statistical definitions may not correspond identically to other existing definitions used by other organizations or governments.

a) Postsecondary Programs

This program cost group includes all direct expenditures incurred in providing instruction to students enrolled FULL-TIME or PART-TIME in postsecondary programs offered by Colleges/Institutes (see section III). These programs are of two kinds: university transfer programs and semi-professional career programs.

b) Trade and Vocational Programs

This program cost group includes all direct expenditures incurred in providing instruction (or training) to students (or trainees) enrolled FULL-TIME in vocational programs at the trade level for credit towards a recognized standing of proficiency or certification. Also included are direct expenditures related to students enrolled in academic upgrading programs for entry into a vocational program. Such students normally attend regular day classes in provincial trade schools, trade or industrial divisions of community colleges, adult vocational centres and other similar schools. These programs or courses prepare the student (trainee) for an occupational role below the professional or semi-professional level. A period of less than one year is normally sufficient to complete courses at this level. For less complex occupations, a program may last only a matter of weeks. Completion of grade 9 or 10 is usually required for entrance to these courses.

Included are, for example, pre-employment programs, language, skill or academic upgrading programs, refresher courses, apprenticeship programs, training on the job or training in-industry programs associated with educational institution, nursing assistant, etc..

c) Continuing Education Programs

This program cost group includes all direct expenditures incurred in providing instruction to students enrolled PART-TIME in courses, mostly in the evening, offered under the auspices of subsidiary divisions of schools designated by various names such as Division of Continuing Education, Adult Education Division and so on. Excluded are activities which have no sustained instruction or educational purpose such as recreational activities, presentations in the performing arts, art exhibitions and displays, debates fairs, conferences or conventions of clubs or associations.

Included are, for example, courses such as pre-employment programs, language, skill or academic upgrading programs, refresher, professional development, general interest, etc., which are offered on a PART-TIME basis.

2. Funds

a) Operating

This fund accounts for the cost of credit and non-credit instruction, non-sponsored research, academic support services, administration, plant maintenance and other operating expenses of the institution financed by fees, grants and other operating income. This fund will normally include all revenues and expenses regarding materials, supplies or services that are consumed within the year and which the institution considers to be operating, within the functional operating areas referred to in section 3 below.

b) Sponsored Research

Sponsored Research is a restricted fund that accounts for income and expenditures for all sponsored research as well as Research and Development (R&D). For an activity to qualify as R&D, there must be an appreciable element of novelty. Income is to be reported following the funds flow approach.

Sponsored Research covers the following activities:

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

Applied Research is the original investigation undertaken to acquire new knowledge, and directed primarily towards a specific practical objective;

Experimental Development is systematic work drawing on existing knowledge gained from research and/or practical experience that is directed to producing new materials, products or devices, installing new processes, systems and services, or improving those already installed.

The following activities should not be counted as R&D:

• all education and training of personnel; however, research by graduates and postgraduate students should be counted;
• scientific and technical information services such as collecting, coding, recording, classifying, analyzing, disseminating, translating, and evaluating, except where conducted solely or primarily for R&D support;
• routine testing of materials, components, products, processes, soils, etc.;
• maintenance of national standards;
• administrative and legal work connected with patents and licenses;
• investigations of proposed engineering projects using existing techniques; however feasibility studies on research projects are part of R&D;
• policy-related studies at the national, regional and local levels, as well as those of business enterprises in pursuit of economic activity;
• routine software development, computer maintenance, quality assurance, routine data collection, and market research;
• the many steps other than R&D necessary for the development and marketing of a manufactured product;
• the raising, management, and distribution of R&D funds; and
• routine investigation and normal application of specialized medical knowledge.

Sponsored Research accounts for the institution's income paid in the form of a contract (legally enforceable arrangements under which the institution, or an individual within the institution, agrees to undertake a research project, using the institution's facilities and/or personnel, for a sponsor that provide funds to meet all or part of the costs of the project) or a grant (unconditional payment for which service is not necessarily expected) from a source external to the institution.

Income sources include government, private industry and donors. Income may also include investment income, if the corresponding expenditures are reported in Sponsored Research.

Expenditures include activity funded from Sponsored Research income and exclude activity funded from the General Operating fund. It also includes the purchase of capital assets, if the corresponding income is reported as Sponsored Research.

c) Capital

The uniform reporting practice in the annual return for capital expenditures is to follow the funds flow approach, rather than to capitalize and amortize. Funds received to acquire capital assets are reported as income in the period in which the funds are received or receivable. Funds used to acquire capital assets are reported as expenditures in the year they take place.

For reporting purposes, capital expenditures are to be reported in the same fund as the corresponding income. Specifically, capital expenditures are only reported in the Capital fund when the corresponding income is reported in the Capital fund.

It is a restricted fund that accounts for resources provided to the institution for capital purposes and not reported in any other fund. Fund income includes grants and related investment income, donations and other resources made available to the institution by external funding sources, such as government and donors, specifically for capital purposes. Fund expenditures include building programs, acquisitions of major equipment and furniture, major renovations and alterations, space rental and buildings, land and land improvements.

Capital expenditures, as well as related revenues, being financed by a Government Department or Ministry other than the one responsible for the institution must be included in this report. The reporting officer should be responsible for obtaining and providing this information.

3. Functions (Schedule 2A)

a) Instruction and non-sponsored research

This includes all direct costs related to credit and non-credit courses, summer courses, extension programs and all other academic functions related to instruction and non-sponsored research such as offices of academic department heads, audio-visual services, laboratories, etc..

b) Library

This includes all the operating costs of the main library as well as the campus libraries, if there are any. All costs of library acquisitions from the Operating fund should be shown under this function.

c) General Administration

This includes costs for activities whose primary function is to provide administrative support for the operation of the institution. It includes the activities of the president's office, vice president, registrar, finance, personnel, public relations, secretariats, etc.. It also includes expenditures on convocations, ceremonies, legal and audit fees, long distance phone calls, the internal portion of debt repayments and costs for computing facilities.

d) Physical Plant

This includes the costs related to physical facilities, such as physical plant offices, maintenance of buildings and grounds, fire insurance, telephone service, security, repairs and furnishing, renovations and alterations, mail delivery service.

e) Student Services

This includes costs for activities whose primary purpose is to assist students in their educational or employment pursuits and which are outside of, but supplemental to, the instruction of academic programs. It includes the costs of: counselling, placement, health services, athletics (not physical education), student accommodation services (not residences), student transportation services, bursaries, scholarships and prizes, student financial aid office, cultural activities, etc..

4. Types of Income

a) Government Grants and Contracts

Lines 1 to 10 include grants from, and contracts with, federal government departments and agencies, provincial/territorial government departments and agencies, and municipal governments.

Government grants provide financial support to institutions and the grants may or may not be restricted.

Government contracts provide financial support to institutions under certain stipulations and conditions, including the provision of a deliverable product, such as a piece of equipment, a service or a report. A contract normally includes provisions for institutions to recover certain indirect or overhead costs, with the contract specifying or documenting the basis for the calculation of the recoverable costs.

Federal

Lines 1 to 6 include all research grants, research contracts, grants and contributions from the Government of Canada and its departments and agencies. Income received from the five major federal government agencies is reported on lines 1 to 5 as applicable.

The line items under "Federal" are as follows:

Provincial/Territorial

Lines 7 to 9 include income from provincial government departments and agencies. For example, Provincial/Territorial CFI matching grants, Provincial/Territorial CFI matching income (line 8) from the Ministry responsible for the institution is reported under the Sponsored Research fund.

In the case of a provincially/territorially administered institution, direct provincial funding is to be included here.

Municipal

Examples of income to be reported on this line include grants from urban transit, communication and parking authorities.

b) Fees

This includes all mandatory student fees for credit and non-credit courses (with the exception of residence fees, parking fees and other similar fees which should be reported under 'ancillary enterprises - gross') paid by, or on behalf of all FULL-TIME and PART-TIME students.

All other fees charged to students such as laboratory fees, transcript, late registration, application, athletic fees, etc., are to be reported under the heading 'other'.

Normally, whenever revenues from fees are reported in Schedule 1 under specific program(s), related expenditures should be reported for the corresponding program(s) in Schedule 2B.

Note: Fees that are "flow through" (such as student activity fees collected for the students' council, etc.) should not be reported as college revenue.

c) Bequests, Donations, Non-Government Grants

This includes receipts from business, industry, foundations, individuals and religious organizations, as well as the value of services donated by various organizations.

d) Investment Income

This includes income from all investments such as dividends, bonds, mortgages, short-term notes and bank interest. Realized gains (or losses) should also be included if they are treated as income in the operating and/or capital funds.

e) Ancillary Enterprises (gross)

This includes total revenues from all ancillary enterprises such as residence or parking fees, and sales of services and products from bookstores, food services (dining hall, cafeterias and vending machines), publishing, laundry services, etc..

It should also be noted that the reporting officer is asked to report, on Supporting Schedule A, a breakdown of total income for the institution's ancillary enterprises.

f) Borrowings

This includes only those borrowings which are used to finance expenditures when repayment is to be made by the institution. Note that borrowings should be reported on an accrual basis.

g) Miscellaneous

This includes net income from rentals (other than ancillary enterprises), library fines and fines for other similar charges, and any income not reported elsewhere.

h) Interfund Transfers

When income from one fund is used to finance expenditures in another fund, report the amount as an interfund transfer. Total interfund transfers must net to zero.

5. Types of Expenditures

a) Salaries and Wages

Salaries and wages (excluding fringe benefits) as well as payments for leave of absence, shown under the appropriate functions and programs, are to be broken down into the following two categories:

b) Fringe Benefits

This includes the institution's contribution (in respect of all salaries and wages) to pensions, group life insurance, workmen's compensation, unemployment insurance, Canada pension, salary contribution insurance, long term disability insurance and other similar benefits. Also include staff development costs paid for by the institution.

c) Library Acquisitions

This includes all purchases of books, periodicals, audio/visual material and other reference material for the library. Costs of binding may also be included if normally considered part of the acquisition costs.

d) Operational Supplies and Expenses

This includes all expenditures for supplies which are normally consumed in the fiscal year, including postage, teaching supplies, photocopying, publications, long distance telephone charges, repair materials, all supplies to operate laboratories, etc..

e) Utilities

This includes all expenditures for fuel, electricity, water, gas, telephone equipment rental, etc..

f) Furniture and Equipment

This includes all expenses for furniture and equipment, such as laboratory equipment (other than consumables), administrative equipment and furnishings, copying and duplicating equipment, computing equipment maintenance equipment, etc.. Rental and maintenance costs as well as other related operating expenses should be shown under the appropriate operational function. Costs for replacing or acquiring new furniture and equipment should be reported under the capital fund.

g) Scholarships and Other Related Students Support

This includes all payments to students including scholarships, bursaries, prizes, fee remissions, gifts, etc..

h) Fees and Contracted Services

This includes all expenses for services contracted to external agencies (except for renovations, alterations and major repairs). Examples would be cleaning contracts, security services, snow removal, etc.. Also included are fees paid to legal counsellors (including retainers for negotiations of collective contracts), auditors' fees, consultant's fees, etc..

i) Debt Services

This includes all payments made to service debts of the institution such as bank interest, mortgage or debenture interest payments, and related charges. Principal payments on loans, mortgages, debentures or repayable grants should be excluded.

j) Buildings

This includes all capital expenditures which are normally considered part of construction costs, except for furniture and equipment as well as land and site services which are to be reported under their respective item. Costs for space rental, building insurances, taxes, minor renovations and alterations on buildings, and all other related operating expenses should be shown under the Physical Plant operational function. Depreciation is not to be included as an expenditure.

k) Land and Site Services

This includes capital expenditures on acquisitions of and improvements to land such as landscaping, sewers, tunnels, roads, etc.. Capitalized professional fees and planning costs related to this category are also to be included. Rental, maintenance and insurance costs as well as other related operating expenses for this item should be shown under the Physical Plant operational function.

l) Miscellaneous

This is to be used when the institution has an operating or capital expenditure not classified in the other categories.

m) Transfers To/From

This item is used for internal transfers of costs between funds or functions whenever it is not feasible to directly adjust the appropriate expenditure items.

The total internal transfers of costs should net to zero.

n) Ancillary Enterprises (gross)

Includes all gross expenditures incurred in the operating of ancillary enterprises (see section 4 (e) above).

It should be noted that the reporting officer is asked to report, on the Supporting Schedule A, a breakdown of total expenditures for the institution's ancillary enterprises.

VIII. Supporting Schedule A

Additional information is to be provided in this section for the total revenue and expenditures of institutional ancillary enterprises (bookstores, residences, food services and parking).

IX. Suggestions

Statistics Canada would welcome any suggestions made to improve this survey.

Canadian Centre for Education Statistics

This information is collected under the authority of the Statistics Act, Revised Statutes of Canada, 1985, Chapter S19.

Confidential when completed

Voluntary survey

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.

Survey purpose

Results from this survey allow users a better understanding of the financial position (income and expenditures) of all community colleges and public vocational schools 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.

Financial Year Ending: Day, Month, Year (2024)

Identification of the institution

• Name of institution
• Address (number and street)
• City
• Province
• Postal code
• Check the appropriate boxes
  • Type
    • Public
    • Private
  • Governing authority
    • Province or territory
    • Board

Identification of the reporting officer

• Name and title of reporting officer
• Address (number and street)
• City
• Province
• Postal code
• Email address
• Telephone number
• Fax number
• Signature of the reporting officer
• Day, Month, Year

Does your institution offer courses at the elementary-secondary level, other than those academic upgrading courses such as Adult Basic Education which should be reported in this questionnaire?

• Yes
• No

If yes, please exclude revenues and expenditures relating to that level of education.

Instructions

1. Please read the guidelines carefully.
2. All amounts should be expressed in thousands of dollars ($'000).
3. Indicate estimated amounts with an asterisk (*).

Affiliated institutions or campuses included in this report

Affiliated institutions or campuses partially included in this report

Affiliated institutions or campuses excluded from this report

Schedule 1 – Operating, Sponsored Research and Capital Income
Table summary
This is an empty data table used by respondents to provide data to Statistics Canada. This table contains no data.

Types	Funds
	Operating ($'000)	Sponsored Research ($'000)	Capital ($'000)	Total ($'000)
Government Grants and Contracts
FederalSchedule 1 footnote *
1. Employment and Social Development Canada (ESDC)
2. Canada Foundation for Innovation (CFI)
3. Canadian Institutes of Health Research
4. Natural Sciences and Engineering Research Council of Canada
5. Social Sciences and Humanities Research Council
6. Other federal
Provincial
7. Regular Grants
8. CFI Matching Fund
9. Other
10. Municipal
Fees
11. Postsecondary Programs
12. Trade Vocational Programs
13. Continuing Education Programs
14. Other
Bequests, Donations, Non-Government Grants
15. Business Enterprises and Individuals
16. Non-profit Organizations and Foundations
17. Sub-total
18. Investment Income
19. Ancillary Enterprises (Gross)Schedule 1 footnote **
20. Borrowings
21. Miscellaneous
22. Interfund TransfersSchedule 1 footnote ***
23. Total Income
Schedule 1 footnote * As highlighted in Section VI.4 in the Guidelines, amounts reported here should relate only to payments received directly by the institution. Return to Schedule 1 footnote * referrer Schedule 1 footnote ** Total should correspond with figures reported in the supporting schedule A. Return to Schedule 1 footnote ** referrer Schedule 1 footnote *** Total interfund transfers must equal to zero. Return to Schedule 1 footnote *** referrer

Schedule 2A – Operating, Sponsored Research and Capital Expenditures by Function and by Type
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
	Operating						Sponsored Research ($'000)	Capital ($'000)	Total ($'000)
	Instruction and non-sponsored researchSchedule 2A footnote * ($'000)	Library ($'000)	General Administration ($'000)	Physical Plant ($'000)	Student Services ($'000)	Total Operating ($'000)
Salaries and Wages
1. Teachers
2. Other
3. Fringe Benefits
4. Library Acquisitions
5. Operational Supplies and Expenses
6. Utilities
7. Furniture and Equipment
8. Scholarships and Other Related Students Support
9. Fees and Contracted Services
10. Debt Services
11. Buildings
12. Land and Site Services
13. Miscellaneous
14. Transfers to/from
15. Ancillary Enterprises (Gross)Schedule 2 footnote **
16. Total Expenditures
Schedule 2A footnote * The figures in this column should be identical to the appropriate ones in column 5 (column total), schedule 2B. Return to Schedule 2A footnote * referrer Schedule 2A footnote ** Total should correspond with figures reported in the supporting schedule A. Return to Schedule 2A footnote ** referrer

Schedule 2B – Direct Instruction Expenditures by Program Cost Groups
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	Programs
	Postsecondary Programs		Trade and Vocational Programs ($'000)	Continuing Education Programs ($'000)	TotalSchedule 2B footnote * ($'000)
	University Transfer ($'000)	Career ($'000)
Salaries and Wages
1. Teachers
2. Other
3. Fringe Benefits
4. Operational Supplies and Expenses
5. Furniture and Equipment
6. Fees and Contracted Services
7. Miscellaneous
8. Transfers to/from
9. Total Instruction Expenditures
Schedule 2B footnote * The figures in this column should be identical to the appropriate ones in column 1 (column instruction and non-sponsored research), schedule 2A. Return to Schedule 2B footnote * referrer

Supporting Schedule A – Ancillary Enterprises
Table Summary
This is an empty data table used by respondents to provide data to Statistics Canada. This table contains no data.

	Total Income		Total Expenditures
	Operating ($'000)	Capital ($'000)	Operating ($'000)	Capital ($'000)
Bookstores
Food Services
Residences
Parking
Other
TotalSchedule A footnote *
Schedule A footnote * Total should correspond with figures reported in schedules 1 and 2A. Return to Schedule A footnote * referrer

Observations and Comments
Table Summary
This is an empty data table used by respondents to give their observations and comments. This table contains no data.

Description (Fund, Function, Type of Income, Expenditure)	Comments

In November 2024, questions measuring the Labour Market Indicators were added to the Labour Force Survey as a supplement.

Questionnaire flow within the collection application is controlled dynamically based on responses provided throughout the survey. Therefore, some respondents will not receive all questions, and there is a small chance that some households will not receive any questions at all. This is based on their answers to certain LFS questions.

Labour Market Indicators

ENTRY_Q01 / EQ 1 - From the following list, please select the household member that will be completing this questionnaire on behalf of the entire household.

WFH_Q01 / EQ 2 - At the present time, in which of the following locations [do/does] [you/Respondent name/this person] usually work as part of [your/his/her/their] main job or business?

1. At a fixed location outside the home
2. Outside the home with no fixed location
3. At home

WFH_Q02 / EQ 3 - Last week, what proportion of [your/his/her/their] work hours did [you/Respondent name/this person] work at home as part of [your/his/her/their] main job or business?

1. All hours at home
2. More than half, but not all at home
3. One quarter to half at home
4. Less than a quarter at home
5. No hours at home

EDU_Q01 / EQ 4 - Did [you/Respondent name/this person] attend a school, college or university within the last 12 months?

1. Yes
2. No

PB_Q01 / EQ 5 - Did [you/Respondent name/this person] attend any training, courses, seminars, conferences, or receive any private lessons or instructions outside the regular education system within the last 12 months?

1. Yes
2. No

PB_Q02 / EQ 6 - What type of training was it?

1. Basic reading, writing, or math
2. Computer (hardware or software)
3. Job search
4. To start or run [your/his/her/their] own business
5. Job-specific
6. Occupational health and safety
7. Personal development
8. Second language
9. Personal interest
10. Other

PB_Q03 / EQ 7 - What was the main reason why [you/Respondent name/this person] participated in this training?

1. Only job-related
2. Mostly job-related
3. Mostly for personal or social reasons
4. Only for personal or social reasons

PB_Q04 / EQ 8 - Did [you/Respondent name/this person] pay any costs to take this training?

1. Direct costs
2. Indirect costs
   OR
3. No, [you/Respondent name/this person] did not pay any costs

BB_Q02 / EQ 9 - During the last 12 months, did [you/Respondent name/this person] have the possibility to take formal training, either fully or partially paid for by [your/his/her/their] current employer in [your/his/her/their] main job?

1. Yes, [you/he/she/they] had that possibility
2. No, [you/he/she/they] did not have that possibility

BB_Q01 / EQ 10 - Do any of the following reasons explain why [you/Respondent name/this person] did not participate in any [training outside the regular education system/ training or education] during the last 12 months?

1. No need for [training/training or education
2. Currently enrolled as a student
3. Too busy to take [training/training or education
4. [Training/Training or education is too expensive
5. Personal or family responsibilities
6. The [training/training or education] [you/Respondent name/this person] wanted was not available
7. [You/Respondent name/This person] lacked confidence or felt unprepared
8. For some other reason

Consultative Engagement Objectives

As part of Statistics Canada's modernization journey, the Dissemination Division (DD), in partnership with the Generative AI Enablement Project team, have created a new bilingual AI-powered search tool: "IntelliStatCan" to improve Statistics Canada's website's current search output.

The purpose of this engagement activity is to conduct usability testing with a targeted audience such as researchers who would benefit from this AI tool (i.e., librarians, academic researchers, and AI collaborative networks). This engagement activity will gather user feedback to further inform the development of the tool.

The primary objectives of this engagement are to:

• Assess the tool's capability to find information.
• Evaluate the accuracy of responses to questions.
• Assess if the tool provides the most relevant information.
• Test the user's experience when they use the tool.
• Assess if the tool functions as intended.

How to get involved

If you would benefit from an AI tool and wish to contribute your insights, please contact us at consultativeengagement-mobilisationconsultative@statcan.gc.ca for more details.

Statistics Canada is committed to respecting the privacy of consultative engagement participants. All personal information created, held, or collected by the agency is kept strictly confidential; it 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.