Addendum to the Supplement to Statistics Canada’s Generic Privacy Impact Assessment related to the Education and Labour Market Longitudinal Platform
Date: October 2023
Program manager: Director, Canadian Centre for Education Statistics
Director General, Labour Market, Education and Socio-Economic Well-Being Branch
Original Supplement to the Generic Privacy Impact Assessment
Reference to Personal Information Bank (PIB)
In accordance with the Privacy Act, Statistics Canada is submitting a new institutional personal information bank (PIB) to describe any personal information obtained from the amendment to the Educational and Labour Market Longitudinal Platform, for the purposes of the Statistics Act. The following PIB is proposed for review and registration.
Elementary and Secondary Student Information Systems
Description: This bank describes information obtained from the administrative files of elementary schools and secondary schools. It includes demographic data and information relating to the individual's activities as a student, such as attendance, grades, and successful completion of the program. Personal information in this databank may also include student identifier number, Social Insurance Number (SIN), name, contact information, and socio-demographic information such as date of birth, citizenship, and gender.
Note: In addition to the requirements specified on the Personal Information Request form, individuals requesting information described by this bank must provide the name of the institution, the number assigned to the individual by the institution and the year(s) the individual studied at the institution. Requests for personal information will be forwarded to the institution that originally provided the information.
Class of Individuals:Individuals who attend or attended an elementary and/or secondary (kindergarten – grade 12) education institution located in Canada in a given school year.
Purpose: The personal information is used to produce statistical information on students by province, type of institution, grade, and sex. Personal information, including the Social Insurance Number, is collected pursuant to the Statistics Act (Sections 3, 7, 8, 13) for statistical purposes only.
Consistent Uses: To reduce respondent burden and enhance survey data, Statistics Canada may combine information from education-related administrative data files with other administrative data records, and with survey responses, including but not limited to the Postsecondary Student Information System (StatCan PPU 090), the Registered Apprenticeship Information System (StatCan PPU 083), the T1 Family File (StatCan PPU 111) and the Longitudinal Immigration Database (StatCan PPU 135) for statistical purposes only.
RDA Number: 2018/007
Related Record Number: StatCan ECT 170
TBS Registration: To be assigned by TBS
Bank Number: StatCan PPU 089
Description of changes to the statistical activity
Under the authority of the Statistics ActFootnote 1, Statistics Canada's Canadian Centre for Education Statistics (CCES) is updating the existing Education and Labour Market Longitudinal Platform (ELMLP) to add datasets that pertain to elementary through to secondary school populations. This data that will be obtained from the administrative files of elementary schools and secondary schools aims to expand the scope of the platform which is currently limited to cohorts of college and university students and registered apprentices. The addition of these datasets will show how early education can affect trajectories of students all the way through to the workforce, and beyond, and remains aligned with the original purpose of the ELMLP SPIAFootnote 2.
The Education and Labour Market Longitudinal Platform (ELMLP) is a platform of securely integrable and anonymized postsecondary education and apprenticeship datasets. It is a collaboration between Statistics Canada, Employment and Social Development Canada (ESDC) and participating provincial/territorial Ministries of Education or District School Boards. Data from the ELMLP helps address a wide range of policy questions pertaining to postsecondary student and apprenticeship persistence, completion, mobility, and pathways, and their labour market outcomes over time. The addition of the (supplementary) datasets allows researchers to address a myriad of questions related to, for example, the impact of financial aid and education savings programs on postsecondary participation and outcomes, the experiences of immigrants and international students in the Canadian postsecondary system, and student sociodemographic and family background.
Since its inception, the primary focus of the ELMLP has been on transitions and outcomes of students/apprentices during and after their postsecondary studies, largely because information on elementary and secondary education was available only at the aggregate level. This assessment addresses the submission of elementary through to secondary student-level data to Statistics Canada, and integration with the postsecondary/apprenticeship data. With the inclusion of these data, policymakers have the ability to understand students' entire educational trajectory including the complex ways in which early educational experiences (including socio-demographic factors) can impact later transitions and access to postsecondary education, transitions to the labour market, and long-term social and financial outcomes. The new data provides previously unavailable insight on factors that may affect Canadians' educational trajectory.
This information is of particular importance in helping the education sector isolate factors that contribute to negative educational outcomes for specific groups of students, particularly groups that may face societal barriers, and to develop and monitor programs to support students during their studies, leading to better outcomes for Canadian students and the economy.
The core datasets in the ELMLPFootnote 3 are the Postsecondary Student Information System (PSIS), the Registered Apprenticeship Information System (RAIS) and the T1 Family File (T1FF) (from income-tax data, for all the records that linked to PSIS or RAIS records).
The purpose of the ELMLP is to develop key pan-Canadian longitudinal indicators related to educational pathways; however, the lack of elementary and secondary school data (Kindergarten to Grade 12) represents a data gap. This addendum addresses the addition of elementary and secondary school data from children's and youths' education records as supplementary files to the ELMLP to allow for longitudinal analyses that were not supported by the post-secondary scope of the administrative data collected previously. The new data is collected in the form of administrative records directly from the respective participating provincial and territorial ministries of education or school boards. The data is integrated using the Social Data Linkage Environment (SDLE)Footnote 4 to provide a unique, anonymous identifier number for each record. No personal identifier variables are included in the resulting analytical datasets. Inclusion of this elementary and secondary school data into the ELMLP will allow this longstanding data gap to be addressed.
The analytical datasets will be created for two key purposes: ELMLP as a service and ELMLP data integration:
- ELMLP as a service takes place in a secure Statistics Canada environment, available only to authorized researchers from the participating organizations for analytical purposes and involves data linkageFootnote 5 to existing Statistics Canada datasets. In this case, there will be a pre-defined period of exclusive access to the platform for analysis of the submitted datasets for the respective data providing participant organizations. Currently, data from the Ontario Ministry of Education, the Toronto District School Board, and the Council of Atlantic Ministers of Education and Training fall into the ELMLP as a service use case. Over time there may be additional participants at this level.
- ELMLP data integration occurs after the exclusivity period. The data will be integrated into the platform, at the discretion of the data provider, and made available to all Statistics Canada researchers, and to approved researchersFootnote 6 (as 'deemed employees') through the Statistics Canada Research Data Centers (RDC)s.Footnote 7 Data from the British Columbia Ministry of Education currently falls into this use case. Over time, there may be additional participants at this level as well.
Given the nature of this initiative, the participating organizations, and the nature of their participation (i.e.: moving from ELMLP as a service to ELMLP data integration) may change over time.
Reason for supplement
While the Generic Privacy Impact Assessment and the Supplement to the Generic Privacy Impact Assessment for the Education and Labour Market Longitudinal Platform address most of the privacy and security risks related to statistical activities conducted by Statistics Canada, this addendum addresses any additional privacy concerns originating from addition of personal information about children and youth from elementary and secondary school data.
Necessity and Proportionality
The use of personal information for the Education and Labour Market Longitudinal Platform can be justified against Statistics Canada's Necessity and Proportionality Framework:
- Necessity: Including elementary and secondary school data in the Education and Labour Market Longitudinal Platform is a joint initiative between Statistics Canada and participating provincial/territorial Ministries of Education or District School Boards to expand the analytical potential and impact of existing administrative datasets. The personal information being collected as part of this data is required for a greater understanding of the complete educational pathway from elementary to secondary to postsecondary or apprenticeship training, and eventually, transitions into the labour market.
Integrating these data with other existing datasets addresses a wide range of priority policy questions about student and apprenticeship enrolment, persistence, completion, mobility, educational pathways, and labour market outcomes over time that are not possible to address with the provincial or schoolboard administrative datasets alone. From a policy perspective, many jurisdictions want to know to what extent K-12 education systems are leading students into postsecondary education, principally to gauge skilled workforce development. These questions are currently data gaps that are of the utmost importance to the participating organizations and speak to the mandate of the CCESFootnote 8. Integrating this data into the ELMLP will address the data gaps as the ELMLP facilitates the production and publication of analysis, indicators, and data tables on these topics. The integration of these data is further essential for analyzing elementary and secondary school student transfers between provinces and jurisdictions, where a data gap has also previously existed.
- Effectiveness – Working assumptions: The addition of elementary and secondary school data to ELMLP enhances the analytical possibilities by integrating them with existing data sources that contain contextual and outcome information for postsecondary students and apprentices. These existing data gaps are best filled using administrative records, given their accuracy and the low response burden for the included populations. For example, predictors of postsecondary enrolment via indicators such as prior grades, standardized testing scores, and exceptionalities (e.g., special needs) can be most efficiently determined using administrative data, rather than survey data as it ensures completeness and reduces the burden on Canadians.
While individual schools and many jurisdictions have their own comprehensive student information systems, integration into a national system will expand the scope of coverage and allow the examination of student pathways across jurisdictions. Rates of high school completion can now be determined using several years of existing administrative data rather than waiting for the completion of one or more cycles of a new survey. Overall, the inclusion of the K-12 personal information will allow for a complete view of educational and labour market trajectories and make it possible to derive insights about how specific influences from early education affect them.
The anonymized analytical datasets, available to approved researchers and policy makers in Statistics Canada's RDCs, provide expanded research opportunities to use this rich information to help positively influence the educational trajectory of Canadians through the system, and all the way to the labour market, further enabling new projects with stakeholders and other academic researchers.
- Proportionality: Participation in this project, and at what level, is decided by the participating school boards or provincial/territorial ministry of education, who are entrusted with the personal information and have the legal authority to disclose it to Statistics Canada.Footnote 9 Use of the ELMLP as a service to exclusively conduct analysis on their own datasets does not necessarily mean the data will be integrated into the ELMLP for research and analysis by Statistics Canada and by deemed employees in the RDCs. This decision rests with the originating organization. Data sharing for the ELMLP is covered in relevant data sharing agreements developed pursuant to the Statistics Act and agreed to with each institution which provides appropriate restrictions to the use and disclosure of the data being shared to both support the data sharing and reduce any residual risk to the privacy of affected individuals.
The personal information being added or used in the ELMLP allows Statistics Canada to fill data gaps related to early educational experiences and their impact on long-term outcomes of students. This, in turn, allows policymakers to make data-driven decisions related to educational programming by assessing programming against the long-term outcomes. This type of research has the potential to significantly impact those outcomes positively, improve access to postsecondary education, and generally better outcomes once an individual reaches the labour market. This is an important goal, which speaks directly to Statistics Canada's mandateFootnote 10 as well as that of the participating organizations providing the data.
- Alternatives: There is currently no alternative option for longitudinal performance indicators, such as completion rates, amongst others in the education field that covers the kindergarten to grade 12 population. Integrating administrative data of elementary and secondary students to postsecondary students and registered apprentices is the only current way to perform a greater, in-depth analysis of educational pathway indicators. Currently, no other data sources allow the analysis of the relationships between students' pathways and their outcomes on the labour market on a longitudinal basis.
Surveys are restricted by cost, sample size and the need for more granularity in the data, response rates and less frequent collection. Statistics Canada has observed that response rates to longitudinal surveys decline considerably over time, potentially introducing bias and reducing quality and accuracy.
Mitigation factors
The overall risk of harm to the affected individuals has been deemed manageable with existing Statistics Canada safeguards that are described in Statistics Canada's Generic Privacy Impact Assessment, with particular emphasis on the following measures:
- The data providers will, in the ELMLP as a service, use the data resulting from the SDLE linkage to analyze only their own student population(s).
- These and future microdata linkages will continue to undergo the standard mandatory prescribed review and approval process, which involves the submission of well documented proposals. When such linkages include personal information, a summary of the approved microdata linkage is posted on Statistics Canada's website.
- All researchers who will have access to the data must be deemed employees of Statistics Canada with an approved research project and valid security clearance that have sworn the Oath or Affirmation of Office and Secrecy pursuant to Section 6 the Statistics Act.
- Data access is approved for a specific purpose and period and must occur in a secure setting such as Statistics Canada offices or the Research Data Centres.
- Statistics Canada vets all output for privacy before being removed from the secure environment or released to the public, ensuring that no individual may be directly or indirectly identified.
Conclusion:
This assessment concludes that, with the existing Statistics Canada safeguards, any remaining risks are such that Statistics Canada is prepared to accept and manage the risk.
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.