Public Service Employee Survey (PSES)

Detailed information for 2024

The Treasury Board of Canada Secretariat and Statistics Canada have partnered to administer the 2024 Public Service Employee Survey (PSES). This public service-wide survey is designed to provide information to support the continuous improvement of people management practices in the federal public service.

Data release - June 23, 2025

• Questionnaire(s) and reporting guide(s)
• Description
• Data sources and methodology
• Data accuracy

Description

The Treasury Board of Canada Secretariat and Statistics Canada have partnered to administer the 2024 Public Service Employee Survey (PSES). This public service-wide survey is designed to provide information to support the continuous improvement of people management practices in the federal public service.

The survey results allow departments and agencies in the Government of Canada to identify their areas of strengths and opportunities on topics such as employee engagement, official languages, equity and inclusion, and workplace well-being. Departments and agencies can use the results to benchmark their performance, track progress over time, and develop and refine strategies.

Employee responses contribute to making the public service a better place to work, which in turn leads to better outcomes for Canadians.

Information given by employees may also be used by Statistics Canada for other statistical and research purposes. Although voluntary, employees' participation is important so that the information collected provides the most accurate and complete picture of the public service.

Subjects

• Government
• Industries
• Labour

Data sources and methodology

Target population

The survey targeted employees of organizations in the core public administration and of participating separate agencies listed in Schedules I, IV and V of the Financial Administration Act who were active in the public service on September 6, 2024. Indeterminate, term, seasonal, casual and student employees, as well as Governor in Council appointees were eligible to participate. A list of participating public service agencies for the 2024 PSES can be found in the "Additional documentation" section. Three non-public service agencies also participated in the survey: Royal Canadian Mounted Police (regular and civilian Members who are not public service employees), Global Affairs Canada (Locally Engaged Staff), and National Capital Commission.

• Additional documentation

Instrument design

The content of the 1999 survey was developed by an interdepartmental committee, led by the Treasury Board of Canada Secretariat, with the support of Statistics Canada. In 2002, the survey was modified extensively, retaining 39 questions from the 1999 version. In 2008, the survey underwent a major revision, including changes to the response scale for the majority of questions, which precluded comparisons with results from previous survey cycles. Recent questionnaires have evolved to address current issues and allow for benchmarking with other government employee surveys. The 2024 survey content was developed through extensive consultation with departments and agencies, central agencies, bargaining agents, Human Resources policy groups, functional communities, and employment equity group committees.

The 2024 PSES questionnaire underwent qualitative testing by Statistics Canada's Questionnaire Design Resource Center (QDRC), to ensure that respondents could comprehend the questions, and to ensure that they were meaningful and would yield valid results.

Qualitative testing in the form of one-on-one interviews were conducted virtually with employees. Interviewees included a mix of Public Service employees with different demographic and work-related characteristics, including gender, race, sexual orientation and language of preference. All comments and feedback from qualitative testing were carefully considered and the questionnaire was revised accordingly.

The 2024 questionnaire was formatted as an electronic survey (to be completed online).

Sampling

The 2024 PSES is a census with a cross-sectional design.

Data were collected for all units of the target population; therefore, no sampling was done.

The PSES sample frame was built from lists of employees provided by human resource services from participating organizations. In doing this, they provided a list of fields requested by Statistics Canada to conduct the survey, as well as a list of employees meeting the in-scope population criteria. These lists were verified, cleaned and combined by Statistics Canada to form the final survey frame. The sampling unit was a person.

A total of 93 departments and agencies participated in the 2024 PSES.

Data sources

Data collection for this reference period: 2024-10-28 to 2024-12-31

Responding to this survey was voluntary.

Data were collected directly from survey respondents.

The collection for 2024 was done using an electronic questionnaire. Each department and agency were responsible for providing a complete list of email addresses for their employees. An invitation e-mail was sent to all eligible respondents the week of October 28, 2024. The invitation e-mail included a unique Secure Access Code (SAC) and instructions for respondents to complete their surveys online via electronic questionnaire. A total of 4 reminder e-mails were sent to respondents who had not completed their surveys during the collection period of October 28th, 2024 to December 31, 2024.

As soon as the respondent submitted their completed questionnaire, the data were transferred through Statistics Canada's internal network and then decrypted for processing.

View the Questionnaire(s) and reporting guide(s) .

Error detection

Processing of the data uses the Social Survey Processing Environment (SSPE), a set of generalized processing steps and utilities to allow subject matter and survey support staff to specify and run the processing of the survey in a timely fashion with high quality outputs.

Edits were performed automatically and manually at various stages of processing at macro and micro levels. They included validity, consistency and flow edits. The flow editing ensured that the data set follows the flow of questions in the questionnaire, using a 'top-down' strategy.

Error detection was done through edits programmed into the self-response electronic questionnaire (r-EQ) as well as edits performed at the processing stage.

Imputation

Imputation is a process used to determine and assign replacement values to resolve problems of missing, invalid or inconsistent data. This is done by editing original responses and missing values on the record based on reliable information from other sources. Imputation is done to ensure that a plausible, internally consistent record is created.

In the 2024 cycle of the PSES, imputation was used to correct respondents' department where this information was missing or appeared inconsistent with other information collected for the PSES.

Estimation

Weighting factors for PSES were calculated so that the respondents and population for each department or agency had the same overall distribution with respect to occupational groups. For example, if 20% of the employees in a department or agency were in a particular occupational group, then the weights were calculated such that when tabulating the data, respondents in this occupational group represent 20% of the number of employees for that department.

In other words, the weighting factor compensates for the over- and under-representation of occupational groups within each federal department or agency. For over-represented groups, the weights are set to one, so that each respondent only represents themselves. For under-represented groups, the weights are greater than one, so that each respondent represents, besides themselves, other persons who did not respond. For example, a respondent with a weight of 2 represents 2 persons in the population.

The weighting procedure calculated this factor for each record. This weight must be used to derive estimates from the microdata file. For example, if the number of employees who "Strongly agree" with the statement "I am proud of the work I do" is to be calculated, it is done by selecting the records for those respondents (Q13 = 1) and summing the weights.

Non-response adjustments were also applied to the weights in order to reduce non-response bias.

Quality evaluation

While rigorous quality assurance mechanisms are applied across all steps of the statistical process, validation and scrutiny of the data by statisticians are the ultimate quality checks prior to dissemination. Two validation measures are implemented for PSES. They include: 1) analysis of changes over time and 2) verification of estimates through cross-tabulations.

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects that could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.

Revisions and seasonal adjustment

This methodology type does not apply to this statistical program.

Data accuracy

The Public Service Employee Survey is a census and therefore, there is no error due to sampling. However, the survey is subject to non-sampling errors such as non-response or other non-sampling errors that may occur at almost every phase of a survey operation. Respondents may make errors in answering questions, the answers may be incorrectly captured, and errors may be introduced in the processing and tabulation of the data. If there are employees missing from the employee lists provided by the departments, that could result in coverage error.

For the 2024 PSES, the response rate for the public service departments and agencies was 50.5%.

Quality assurance and control methods were implemented according to Statistics Canada's standard practices at each step of the data collection and processing cycle to monitor the quality of the data. These measures included qualitative testing in the form of one-on-one interviews to detect problems of questionnaire design or misunderstanding of instructions, and using edit rules designed to detect missing, invalid or inconsistent data.

Total non-response occurs when an eligible employee did not participate in the survey or returned a completely blank questionnaire. Total non-response can be a major source of non-sampling error in many surveys, depending on the degree to which respondents and non-respondents differ with respect to the characteristics of interest. Non-response adjustments were applied to the weights in order to reduce non-response bias.