Public Service Employee Survey (PSES)

Detailed information for 2022/2023

The Treasury Board of Canada Secretariat and Statistics Canada are partnering to administer the 2022/2023 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 - May 31, 2023

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

Description

The Treasury Board of Canada Secretariat and Statistics Canada are partnering to administer the 2022/2023 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 will allow federal organizations to identify their areas of strength and concern related to topics such as employee engagement, hybrid workplace, equity and inclusion, and workplace well-being. Departments and agencies will be able to benchmark and track progress over time, and inform the development and refinement of action plans.
Employees are given a unique opportunity to share their experiences and shape the way forward in order to improve the quality of the federal workplace. Better people management practices lead to better results for the public service, and in turn, better results for Canadians.

Your information may also be used by Statistics Canada for other statistical and research purposes. Although voluntary, your participation is important so that the information collected is as accurate and complete as possible.

Subjects

• Government
• Industries
• Labour

Data sources and methodology

Target population

The survey targets active 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. Indeterminate, term, seasonal, casual and student employees, as well as Governor in Council appointees are eligible to participate.

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. The 2005 version was a duplicate of the 2002/2023 PSES. 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 2022/2023 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 2022/2023 questionnaire contains 163 questions: 27 new questions, 8 modified questions, and 128 questions repeated from the 2020 survey.

The new questionnaire underwent qualitative testing by the STC 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, occupational group, department, province/territory of residence and language of preference. All comments and feedback from qualitative testing were carefully considered and the questionnaire was revised accordingly.

The 2022/2023 questionnaire was formatted as an electronic survey (to be completed online).

Sampling

This survey is a census with a cross-sectional design.

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

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

A total of 91 departments and agencies are participating in the 2022/2023 survey.

Data sources

Data collection for this reference period: 2022-11-21 to 2023-02-05

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

The Public Service Employee Survey is administered to active employees in organizations in the federal public service, for which Treasury Board is the employer, as well as in participating separate agencies. The survey is a census with voluntary participation. The collection is done using an electronic questionnaire. Each department and agency was responsible for providing a complete list of email addresses for their department. Email invitations are sent to each employee with a valid email address containing a Secure Access Code (SAC) to access the survey questionnaire. Reminders are sent to those who have not responded to the survey. As soon as the respondent submits their completed questionnaire, the data are transferred through Statistics Canada's internal network and then decrypted for processing. Respondents have the possibility to save their partially completed questionnaire and finish it later.

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

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

Imputation

This methodology type does not apply to this statistical program.

Estimation

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

Put another way, 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 calculates 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 (Q2(d) = 1) and summing the weights.

Non-response adjustments are 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.

Quality assurance and control methods are 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 are applied to the weights in order to reduce non-response bias.