Supplement to Statistics Canada's Generic Privacy Impact Assessment related to UCASS Modernization
Date: August 2022
Program manager: Director, Canadian Centre for Education Statistics,
Director General, Labour Market, Education and Socioeconomic Well-being
Reference to Personal Information Bank (PIB)
PIB draft submitted for review to OPMIC
Description of statistical activity
The Full-time University and College Academic Staff System (FT-UCASS) is an annual survey since 1937 that collects national comparable information on the number and socio-economic characteristics of full-time teaching staff at Canadian universities. Participating universities extract this information from their Human Resource Information Systems (HRIS) for each individual staff member employed by the institution as of October 1st of the academic year. The information is organized on an EXCEL spreadsheet and sent to Statistics Canada through the electronic file transfer system (e-FT). The data collected by this survey are used in a non-identifiable form by a variety of clients with a diversity of needs including conducting studies on employment patterns, gender-based analyses, workforce renewal, salary analysis for contract negotiation and international comparative statistics. We are collecting UCASS under sections 3, 7(1) and 22(h) of the Statistics Act. The UCASS survey is mandatory in accordance with the Statistics Act.
The target population of this data collection is full-time academic teaching staff in degree-granting in 112 institutions (mainly universities) whose term of appointment is not less than twelve months. We are collecting 27 data elements on each full-time academic staff member in each reporting institution such as Unique ID per institutions, Gender, Year of birth, Department, Salary information, Principal subject taught, Rank, Previous employment, Year of appointment to present rank, Type of appointment, Year of appointment to institution, First and highest degree and Country of birth and highest degree.
The data collection was cancelled in 2012 due to budget cuts sustained by Statistics Canada. It was re-instated by Statistics Canada in September 2016 partly due to the interest of the then Minister of Science, who agreed to fund the survey. Following the re-instatement of the survey there has been much interest in closing known data gaps on academic staff in Canadian postsecondary institutions in terms of coverage and content. These gaps include a lack of Equity Diversity and Inclusion (EDI) data on full-time academics, other than gender, as well as information on part time or contract staff.
Over the last year, representatives from the Canadian Centre for Education Statistics (CCES) have engaged in discussions with key postsecondary education stakeholders who are also interested in closing these data gaps and modernize UCASS through a feasibility study. These include Dimensions: Equity, Diversity and Inclusion Canada (which aims to assess and promote filling equity gaps in postsecondary institutions), Innovation, Science and Economic Development Canada, the three granting agencies (Natural Sciences and Engineering Research Council, Social Sciences and Humanities Research Council, and Canadian Institutes of Health Research) and the Canada Foundation for Innovation. In addition, CCES has recently been approached by the Inter-Institutional Advisory Committee also about the inclusion of EDI data within FT-UCASS to support the Scarborough Charter on anti-Black racism and Black inclusion.
Before initiating a complete data collection for all universities within the UCASS-FT survey frame on EDI variables and contract staff, the Canadian Centre for Education Statistics has proposed to conduct a pilot project on a sample of universities in the UCASS survey frame that includes:
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Adding EDI to the current collection and dissemination of FT-UCASS;
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Assessing the feasibility and efficiency of collecting additional personal identifiers (first name, last name and date of birth) within FT-UCASS to explore data integration with the Canadian Census and other data sources to obtain their EDI characteristics and;
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Expand coverage to include part-time/contract staff (PT-UCASS).
Specifically, we are proposing to explore in this feasibility study a new data collection for part-time academics with data elements including:
- first name,
- last name,
- date of birth,
- EDI information (see below),
- department,
- subject taught,
- type of contract (sessional, limited term contract, overload and other)
- salary information,
- contract start and end date,
- teaching load,
- number of courses taught,
- number of credits taught, and
- number of contract hours.
EDI information is of interest because it can be used to identify and eliminate obstacles and inequalities and encourage participation of designated underrepresented groups within the academic community. Collecting variables related to the following categories will support the overall goal of increasing the representation of the following groups among academic staff:
- Women
- Indigenous People
- Persons with disabilities
- Member of visible minority/racialized groups
- Members of the LGBTQ2+ communities
- Individuals who identify as or belong to more than one of these groups.
This pilot would be conducted in selected Canadian universities and would allow us to test an expanded data collection strategy. This information would inform the development of a permanent collection of these variables within the UCASS data collection. The pilot project would be most effective if there were a balanced mix of institution types: large, medium, and small institutions, as it is expected that there may be different challenges from each.
If the pilot project was deemed successful, the next step would be to negotiate ongoing funding to modify FT-UCASS, and/or to create PT-UCASS surveys for all institutions in the current UCASS data collection frame.
This pilot project will be conducted in selected Canadian universities who are currently part of the Dimensions' cohort and included in the UCASS survey data collection, to test this expanded data collection strategy. Statistics Canada is also approaching other UCASS institutions to seek interested parties that could contribute to this exercise and/or would be willing to be part of the pilot project and the consultation process.
The following universities are part of the Dimensions' cohort and will be invited to participate in our pilot project. We are presently evaluating the following Dimension's cohort universities to assess their eligibility and willingness to participate in our pilot project.
- Mount Saint Vincent University (Nova Scotia),
- Ryerson University (Ontario),
- Simon Fraser University (British Columbia),
- Université Laval (Québec),
- University of British Columbia (British Columbia),
- University of Calgary (Alberta),
- University of New Brunswick (New Brunswick),
- University of Ottawa (Ontario),
- University of Saskatchewan (Saskatchewan),
- University of Winnipeg (Manitoba),
- Vancouver Island University (British Columbia),
- Wilfrid Laurier University (Ontario)
Reason for supplement
While the Generic Privacy Impact Assessment (PIA) addresses most of the privacy and security risks related to statistical activities conducted by Statistics Canada, this supplement is required before initiating data collection due to the sensitivity of the information being collected. Given this is a pilot, it will also inform the ongoing survey as to how best to proceed with adding the EDI variables. Statistics Canada treats all collections of sensitive personal information very seriously and this assessment will assure that it is being done in the most privacy protective way feasible.
Necessity and Proportionality
The collection of personal information for UCASS can be justified against Statistics Canada's Necessity and Proportionality Framework:
1. Necessity:
A data collection on EDI and contract staff on university academics is necessary to support enhanced statistics on diverse populations, and support the government's, non-government organizations' and society's efforts to address systemic racism, gender gaps—including the power gaps between men and women—and bring fairness and inclusion considerations into decision making. Ultimately, the collection of more robust disaggregated data on the under-represented groups within the academic community (EDI and part-time/contract staff) will contribute to a more equitable employment environment in Canadian universities. This would include an environment where research funds are distributed according to how the groups under consideration are represented in the Canadian population and the academic community. It would also allow to inform the extent by which work precarity exists within the academic teaching community.
Furthermore, there is also consensus among key stakeholders related to this project that in order to improve the representation of the EDI groups within academia, having data that conforms to Statistics Canada's standards on these characteristics is a first step. Data on the characteristics of academic staff can be compared to benchmark data from Statistics Canada sources (Census, Canadian Survey on Disability, Survey on Postsecondary Faculty and Researchers) and over the long term, measuring progress toward a more representative academic community across universities.
In recent years, the federal research funding agencies have undertaken several initiatives to foster a more equitable, diverse and inclusive research ecosystem in Canada. The underlying premise is that in order to achieve world-class research, systemic barriers must be addressed that limit the full participation of all talented individuals
The Canadian Institutes of Health Research (CIHR), the Natural Science and Engineering Research Council of Canada (NSERC), the Social Sciences and Humanities Research Council of Canada (SSHRC) , under the leadership of the Canada Research Coordinating Committee (CRCC), have developed an action plan that will guide initiatives and decisions to contribute to a system-wide transformation.
This Action Plan outlines measures to increase equitable and inclusive access to granting agency funding opportunities. It also details how the granting agencies can influence the achievement of an inclusive post-secondary research system and culture in Canada. However, in order to measure progress, quality data on the representation of the under-represented groups in the research eco system in Canada is required. Currently, some of the research agencies are using data from the US and UK since comparable Canadian data is not available.
Most large Canadian universities are required to have a Canada Research Chairs Action Plan which lays out a road map that the institutions plan to use that will be used to meet their EDI targets. Conducting a pilot will allow Statistics Canada to evaluate if the collected data is sufficient to meet this goal or if additional or potentially fewer data elements are required if the collection were to be expanded to all institutions.
2. Effectiveness - Working assumptions:
The goal of the pilot project is to analyze the benefits and disadvantages of collecting EDI information (visible minority status, Indigenous identity, disability status, gender identity, sexual orientation) on university academic staff either through data integration or by direct collection from the universities' internal collection on EDI. We also want to assess the feasibility and efficiency of collecting additional personal identifiers (first name, last name and date of birth) to explore data integration with the Canadian Census and other data sources to obtain or derive their EDI characteristics. This could be an option for smaller institutions in the pilot that have less resources to collect and provide STATCAN EDI data for their academics full-time or part-time or have obtain low coverage while collecting it.
There have been a number of challenges identified for the collection of data from the institution's internal data holdings. In the last round of consultations on the expansion of UCASS, there was a consensus that this expansion would be of great interest. However, one of the challenges is that for those that have established EDI data collections, they may have to re-open the agreements under which the data was originally collected to seek permission to share this information with Statistics Canada. This information is self-reported by academic staff to the institution and not all individuals choose to report EDI characteristics for various reasons (fear of reprisals from employer, fear of being blocked from achieving tenure and movement through the ranks, inherent bias etc.). Some EDI information may be more sensitive, such as gender identity, sexual orientation or disability status. Data reported to UCASS comes from Human Resource systems, it may be that some university academics would not want their self-identified EDI information attached to the human resources records. Therefore, data linkage using personal identifiers could mitigate this challenge.
Once the results of the pilot project have been analyzed, then an approach to collection within the full frame of UCASS can be recommended. Depending upon the results of the analysis, a hybrid approach to the collection of EDI characteristics could be adopted for the full frame:
- for those universities that are able to report the EDI information that this could be done directly and,
- for those universities that do not have an established EDI collection in place or that the mechanism under which the EDI data are collected does not permit sharing with Statistics Canada, the collection of personal identifiers to facilitate data linkage with the Census could be an option.
During the 1990's, Statistics Canada collected data on part-time university teaching staff with limited success. Some of the challenges included that part-time academic staff were not unionized and the impetus to collect information on them by institutions was not as critical. As well, the definition of part-time staff in the survey was also not clear and well understand by respondents.
3. Proportionality:
A data collection on EDI and contract staff on university academics will support enhanced statistics on diverse populations, and support the government's, non-government organizations' and society's efforts to address systemic racism, gender gaps—including the power gaps between men and women—and bring fairness and inclusion considerations into decision making. Ultimately, the collection of more robust disaggregated data on the under-represented groups within the academic community (EDI groups and part-time/contract staff) will contribute to a more equitable employment environment in Canadian universities. This would include an environment where research funds are distributed according to how the groups under consideration are represented in the Canadian population and the academic community. It would also allow to inform the extent by which work precarity exists within the academic teaching community. While, these added variables are sensitive, the pilot will allow us to assess the proportional benefit of them especially with respect to the risk to privacy for these academics.
As well, there is much anecdotal evidence that those academics from the under represented groups suffer a disadvantage in terms of promotions, moving through the ranks and salaries. However, there is no national comparable source of information to evaluate this.
While the interested parties could attempt a data collection on their own, they recognize that Statistics Canada has a proven record of collecting and safeguarding sensitive data. And since the FT-UCASS is an established and well- respected data collection, it is felt that adding EDI questions to this, would facilitate the collection of such data and safeguard the privacy and confidentiality of respondents.
The pilot project will allow Statistics Canada to assess the challenges to reporting and the sensitivity of reporting out such information. Any risk factors that cannot be anticipated, will likely be identified as outcomes of the project. The goal of the pilot project is to seek to collect data from a mix of universities: small, medium and large size and with good geographical representation. It is expected that any challenges arising from this data collection will be identified before a large- scale data collection is launched. The outcome of the pilot project will be to recommend if this data collection is feasible for all universities.
4. Alternatives:
As it stands, there is no centralized data collection on EDI characteristics of academic staff in Canada or on contract staff in postsecondary institutions. A one-time collection of data on Postsecondary Faculty and Researchers cannot be used to establish benchmarks because there was no unified sample frame used in the collection.
The granting agencies (NSERC, SSHRC and CIHR) have a self- identification questionnaire for all Canadian Research Chair applicants. This just a subset of academics in Canadian universities and does not represent the total academic staff in Canada, thereby making it impossible to use this source to establish benchmarks for this population.
While there was a collection on contract staff (part-time faculty) in the 1990's, it was cancelled due to coverage issues. Best practices and lessons learned will be employed from this data collection in the possible implementation of a full -scale data collection if deemed appropriate after the results of the pilot project are analyzed.
The Canadian Association of University Teachers also conducted a one- time study of the number of contract staff by submitting Access to Information requests to universities, however, this approach is not sustainable over the long term.
Provincial associations have done one- time studies of contract staff however, these are sporadic and have not been translated into consistent data collection.
The goal of the feasibility study is to analyze the benefits and disadvantages of collecting EDI information on university academic either through data integration or by direct collection from the universities' internal collection on EDI. As well, it is to determine the parameters and definitions that will be used in defining and collecting data on contract staff in Canadian universities. Information from all existing data collections on such staff will be used to augment the development of the feasibility study and the permanent data collection if deemed feasible.
Mitigation factors
When collected in universities, EDI information is self-reported by academic staff and not all individuals choose to report EDI characteristics for various reasons (fear of reprisals from employer, fear of being blocked from achieving tenure and movement through the ranks, inherent bias etc.). EDI information is generally considered sensitive, particularly gender identity, sexual orientation or disability status. Data reported to UCASS comes from Human Resource systems, it may be that some university academics would not want their self-identified EDI information attached to the human resources records. Therefore, data linkage to existing datasets that include this information using personal identifiers could mitigate the intrusiveness of requiring that information to be collected via Human Resource data from the institutions.
The overall risk of harm to the survey respondents has been deemed manageable with existing Statistics Canada safeguards that are described in Statistics Canada's Generic Privacy Impact Assessment, as well as with the following measures: Any information from those universities that participate in the feasibility study would be sent to Statistics Canada by the electronic file transfer system to ensure the security of the data being transferred. Data analysis and processing take place on established Statistics Canada secure networks. At reception, we would create two separate files: UCASS main file (current variables) and UCASS ID file (linkage variables): Unique ID #, gender, Province, first name, last name, date of birth. This file would be used only for assigning an anonymous identifier to be used in a secure data integration environment (SDLE) that would allow data integration with Census or other STC survey to estimate EDI information.
At the outset, the nominal information will be removed from the records and replaced with an anonymized key. The UCASS team would create a dissemination file excluding new personal identifiers variables. We will have each institution in the pilot project (and eventually if successful all institutions in the UCASS survey frame) complete and sign an authorization to release aggregate data by pilot institutions. They would also approve validation tables with EDI specific comparators (Census-NOC-CMA). Additionally, staff identifiers would be replaced with a randomly generated synthetic identifier as part of the regular production process for UCASS.
There is a low risk that those academics who have identified as being in the under-represented groups could be identified due to small numbers, the size of institution or because of geographic disaggregation (e.g. there is only one university in Newfoundland and Prince Edward Island) if these new data elements were to be include on the UCASS file accessible in Statistics Canada research data center. The purpose of the pilot project is to look at the data collected and analyze the outcomes to determine the most secure way to disseminate such information if a wide-scale collection is implemented. However, a plan of action cannot be established until results have been collected and analyzed. Any further mitigations will be identified during this pilot phase with a view to implement them before the project goes into full production.
Conclusion
This assessment concludes that the risk is deemed manageable by Statistics Canada and there is no privacy impediment for this pilot to go ahead. Further, an SPIA that covers this activity in its entirety will be conducted in the event that this becomes a regular survey.
Formal approval
This Supplementary Privacy Impact Assessment has been reviewed and recommended for approval by Statistics Canada's Chief Privacy Officer, Director General for Modern Statistical Methods and Data Science, and Assistant Chief Statistician for Social, Health and Labour Statistics.
The Chief Statistician of Canada has the authority for section 10 of the Privacy Act for Statistics Canada, and is responsible for the Agency's operations, including the program area mentioned in this Supplementary Privacy Impact Assessment.
This Privacy Impact Assessment has been approved by the Chief Statistician of Canada.