Supplement to Statistics Canada's Generic Privacy Impact Assessment related to the Education and Labour Market Longitudinal Platform

Date: March 2019

Program manager: Director, Tourism and the Centre for Education Statistics Division


The Education and Labour Market Longitudinal Platform (ELMLP) is an environment that allows the integration of variables from core education-related administrative sources with those from other selected datasets. The ELMLP does not contain any personal identifiers. Anonymous linkage keys are created using the Social Data Linkage Environment (SDLE) for which a separate privacy impact assessment has been done (Social Data Linkage Environment).

Reference to Personal Information Bank

In accordance with the Privacy Act, Statistics Canada has registered Personal Information Banks (PIBs) for its holdings of personal data, including the core datasets which will be linked through the ELMLP: the Postsecondary Student Information System (PSIS) (PPU 090), the Registered Apprenticeship Information System (RAIS) (PPU 083), and the T1 Family File (T1FF) (PPU 111). The use of personal information from these programs for linkage purposes is described in these PIBs as part of the consistent uses.

When supplementary data sources are integrated into the ELMLP, the relevant PIBs are added or updated as required.

Please refer to 'Information about Programs and Information Holdings' on the website for descriptions of these Personal Information Banks.

Reason for supplement

Statistics Canada's Generic Privacy Impact Assessment (PIA) presents and addresses the privacy principles and levels of potential security risks related to its statistical activities. Existing safeguards have been assessed as sufficient to address the potential privacy risks associated with the ELMLP.

The purpose of this PIA supplement is therefore to describe this new data environment and to clearly illustrate the need for this use of personal information in order to address any concerns Canadians might have about this statistical activity.

Description of statistical activity

The Education and Labour Market Longitudinal Platform (ELMLP) is a platform of securely integrated datasets from which analytical variables will be accessible for research purposes using anonymous matching keys. The ELMLP provides access to anonymized longitudinal information about cohorts of college and university students and registered apprentices, to better understand their pathways through the postsecondary education system and how their education and training affects their career prospects in term of earnings.

Research using data from the ELMLP will address a wide range of policy questions pertaining to student and apprentice persistence, completion, mobility and pathways. These data will allow policy makers to understand the different types of trajectories that students can take through their postsecondary education or apprenticeship training as well as student characteristics that may be related to these trajectories. The data can also be used to inform policy questions related to labour market outcomes such as which postsecondary experiences and outcomes are related to better labour market outcomes, and how student characteristics (personal or family-related) may be related to their labour market outcomes. The results produced through the ELMLP will also be useful to young Canadians and their families when they make decisions related to future education.

The core datasets in the ELMLP 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 and/or RAIS records). PSIS is a data holding of all public Canadian college and university enrolments and graduates by type of program and credential, and field of study for each school year. RAIS is an administrative dataset of annual pan-Canadian (provincial and territorial) data on registered apprentices and trade qualifiers. The core ELMLP consists of PSIS data from 2009 onwards, RAIS data from 2008 onward, and T1FF data from 1992 onwards for all provinces and territories.

In order to address additional related research questions, further datasets can be integrated to the ELMLP using the SDLE described in more detail below. Personal Information Banks for these new datasets will be added or updated as required.

The personal identifiers obtained for postsecondary students and apprentices are used in the SDLE to assign the anonymous statistical identifiers that allow Statistics Canada to link to other sources of information for statistical analysis and research, once approval has been obtained in accordance with the Directive on Microdata Linkage. The personal identifiers obtained are removed from the rest of the information and securely stored with restricted access to no more than twenty-five Statistics Canada employees with an approved operational requirement to access them, and whose access is removed when no longer required. The retention period for their storage and their destruction is prescribed by Statistics Canada's Directive on the Management of Statistical Microdata Files. Under no circumstances will the students' personal information obtained from postsecondary and apprentice institutions be used for administrative or analytical purposes.

The integrated datasets in the ELMLP are subject to the confidentiality requirements of the Statistics Act. As with all data collected under the Statistics Act, the integrated analytical datasets available for research do not contain any personal identifiers. Access is granted to researchers who have been deemed as Statistics Canada employees after they have obtained a security clearance and have sworn an oath of confidentiality under the Statistics Act. Data access is approved for a specific purpose and for a specified period of time, and must occur in a secure setting such as Statistics Canada offices or the Research Data Centres. Statistics Canada vets all output for confidentiality before removal from the secure setting or release to the public.

Only aggregated and non-confidential statistical information on Canadian students and apprentices will be made publically available and as such, individuals will not be identifiable in any product disseminated to the public. No personal information would ever be disclosed without consent of the original data collector and the authorization from the Chief Statistician, as required by the Statistics Act.

Results obtained using the ELMLP are available to Canadians through a variety of products, such as data tables and analytical reports, released by Statistics Canada. Examples of how results will benefit Canadians include: by providing information to prospective students and registered apprentices on income earnings by field of study and trade; by providing insight on student education pathways which can be used by policy makers to develop programs to be best support students during their studies; and by providing insight into student family and background characteristics that influence postsecondary education participation and completion which can be used by policy makers to inform policy decisions related to maximizing postsecondary participation and success.

Necessity and Proportionality

The use of personal information for the ELMLP can be justified against the four-part test proposed by the Office of the Privacy Commissioner of Canada:

  1. Necessity: The Education and Labour Market Longitudinal Platform is a joint initiative of Statistics Canada, Employment and Social Development Canada and the postsecondary ministries in the provinces and territories to expand the potential of existing administrative datasets. The ELMLP enables the integration of different datasets, both longitudinal and cross-sectional, to help address a wide range of priority policy questions pertaining to student and apprenticeship persistence, completion, mobility, educational pathways and labour market outcomes over time, that were not possible to address with the underlying annual datasets alone. The ELMLP facilitates the production and publication of analysis, indicators and data tables on these topics. The ELMLP is essential for analysis of PSIS and RAIS data longitudinally and between institutions and jurisdictions.

  2. Effectiveness: The ELMLP greatly enhances the analytical possibilities by making PSIS and RAIS longitudinal. Additionally, integrating them with other data sources that contain contextual and outcome information for postsecondary students and apprentices will fill existing data gaps that can only be filled using administrative records. For example, earnings can be compared after the completion of different types of educational or training programs for different types of students using administrative data, rather than survey data – thus greatly reducing the burden on Canadians. Pathways through postsecondary education over time and across institutions and jurisdictions can be examined. Rates of program completion can be determined using several years of existing administrative data rather than waiting for the completion of one or more cycles of a new survey.

    The analytical datasets with anonymous matching keys available to approved researchers (as 'deemed employees') through the Statistics Canada Research Data Centers expand access and research opportunities for using this rich information and enable new projects with stakeholders and others.

  3. Proportionality: Any use of personal information implies some level of perceived intrusion and requires careful management. The methods and practices behind the ELMLP (and the SDLE) have been designed to ensure protection of privacy and personal information, while retaining the ability to integrate analytical variables from different existing sources to fill data gaps.

    In addition to filling data gaps, the development of the ELMLP allows for additional research opportunities using the core datasets to inform policy and practice. By integrating Statistics Canada's current administrative datasets, new and expanded statistical analysis can be undertaken. It also enables future linkage work with other Statistics Canada administrative and survey-based databases – again, enriching and expanding analytical opportunities to better inform public policy and research.

  4. Alternatives: The ELMLP provides the keys to match annual student and apprenticeship records over time. Without this option for longitudinal data, the analysis of student pathways through postsecondary and apprentices' programs is impossible. No longitudinal performance indicators, such as completion rates, can be derived. Matching an administrative data census of postsecondary students and registered apprentices to tax information on earnings allows analysis at a deeper level of education credentials and type of programs, and outcomes beyond education. In an approved secure environment, employees and deemed employees can analyze the relationships between students' pathways and their outcomes on the labour market on an annual basis. No other sources allow such a detailed analysis. Survey sources are restricted by sample size, response rates and less frequent collection, and lack of granularity in the data. A new survey is expensive and carries a response burden. Statistics Canada has longstanding evidence that response rates to longitudinal surveys decline considerably over time, introducing bias and substantially reducing quality and accuracy. For these reasons, most longitudinal surveys have been discontinued.


A summary of this supplemental PIA will be publicly available on the Statistics Canada website as an addendum to the Generic PIA. A series of reference guides describing the ELMLP are available on Statistics Canada website ('Technical Reference Guides for the Education and Labour Market Longitudinal Platform (ELMLP)', (Catalogue number 37200001). Information on datasets available within the ELMLP through Statistics Canada Research Data Centers and on approved ELMLP-based research projects are listed on Statistics Canada website (List of all RDC projects within the last 12 months).

Statistics Canada has worked with the Council of Ministers of Education Canada (CMEC) and the Canadian Council of Directors of Apprenticeship (CCDA), and ESDC, to obtain the policy-driven research questions' priorities. These communications have been used to guide a development of the ELMLP and prioritization of datasets to be added. Statistics Canada is working on a plan to increase transparency on use of administrative data for development of ELMLP and will continue to work with CMEC and CCDA to ensure the effectiveness of the resulting communication material.

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