Canadian Survey on Working Conditions (CSWC)

Detailed information for September 2024 to July 2025

The Canadian Survey on Working Conditions (CSWC) aims to measure all core dimensions of quality of employment—including working time and work-life balance, skills development and training, and security of employment—to better understand how different job characteristics are distributed across the employed population.

Data release - June 17, 2026

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

Description

The CSWC complements data from the Labour Force Survey (LFS) and its supplements to offer a comprehensive picture of quality of employment in Canada. It gathers information from employed Canadians on their work arrangements and working conditions with the aim of providing a better understanding of the quality of employment in Canada as well as the relationship between working conditions and well-being.

Quality of employment is an important issue for society, policy makers, governments, and researchers. Employment is key to the social and economic advancement of workers and provides them with a sense of identity, but it may also be associated with risks for health and well-being.

The CSWC provides information to all levels of governments that can support funding decisions, help identify priorities and plan important programs.

Topics covered by the CSWC include:

- The physical and social environment at work
- Working time quality
- Work intensity
- Discrimination at work
- Training
- Work and life satisfaction
- Use of artificial intelligence and automation
- Job prospects and pensions
- Work-related physical and psychosocial well-being

Reference period: 2024-2025

Collection period: September 23, 2024 to October 18, 2024; December 16, 2024 to January 17, 2025;
March 17, 2025 to April 17, 2025; June 23, 2025 to July 18, 2025

Subjects

• Hours of work and work arrangements
• Job training and educational attainment
• Mental health and well-being
• Wages, salaries and other earnings
• Workplace organization, innovation, performance

Data sources and methodology

Target population

The target population for this survey is a subset of the target population of the LFS. The CSWC specifically samples individuals who indicated that they were employed in the LFS. Excluded from both the LFS and CSWC coverage are persons living on reserves and other Indigenous settlements in the provinces, full-time members of the Canadian Armed Forces, the institutionalized population, and households in extremely remote areas with very low population density. These groups together represent an exclusion of approximately 2% of the population aged 15 and over. In addition, residents of the Yukon, Northwest Territories, Nunavut and those aged 70 or older are excluded from the CSWC.

Instrument design

The questionnaire was developed by Statistics Canada. Experts from the Questionnaire Design Resource Centre carried out qualitative interviews and prepared an evaluation report. All comments and feedback from qualitative testing were carefully considered and incorporated into the survey whenever possible.

Frame:
The LFS selects its sample from the Area Sample Production System Frame. The CSWC samples directly from LFS respondents who have completed their sixth month of participation in the LFS.

Sampling

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

The CSWC is a sample survey with a cross-sectional design administered to a sub-sample of LFS respondents, and therefore its sample design is closely tied to that of the LFS. The CSWC uses the rotation groups that completed their sixth month of participation in the LFS in July, August, September, November, January, February, April or May.

A small number of records are excluded before sample selection begins: respondents with invalid names, imputed records from the LFS, respondents denying Statistics Canada permission to call them, and respondents aged 70 and older.

Among the in-scope records, all of the available LFS sample is kept. In order to reduce the response burden within the household, one person per household is selected.

Sampling unit:
The CSWC inherits the stratified multi-stage design of the LFS. In the LFS, a small contiguous geographical area, called a cluster, is the sampling unit at the first stage. The sampling unit at the second stage is the dwelling. For the CSWC, there is a third stage, where the sampling unit is the person.

Stratification method:
The stratification methodology is the same as the one used for the Canadian Labour Force Survey (Catalogue No. 71-526-X, 2.5 Stratification, available online).

Sampling and sub-sampling:
The LFS uses a probability sample that is based on a stratified multi-stage design. Each province is divided into large geographic stratum. The first stage of sampling consists of selecting smaller geographic areas, called clusters, from within each stratum. The second stage of sampling consists of selecting dwellings from within each selected cluster. The CSWC then selects one employed person aged 15 to 69 per household that completed its sixth month of participation in the LFS.

Total sample size is approximately 9,250 respondents per cycle.

Data sources

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

Household members selected for the CSWC are contacted within seven weeks of their last LFS interview.

Respondents have the option to complete the survey online, or over the telephone with the assistance of an interviewer. If the respondent does not complete the questionnaire online, they will be contacted by an interviewer to complete the survey.

Similar to the LFS, the interviewers are asked to make all reasonable efforts to obtain the CSWC interview. Refusals at first contact are followed up by a senior interviewer.

Proxy response is not allowed in the CSWC.

The CSWC is available in both English and French.

The average time required to complete the survey is about thirty minutes.

To enhance the data from the CSWC and to reduce the response burden, Statistics Canada will combine the information provided in the CSWC with information from the LFS.

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

Error detection

A series of verification steps are performed to identify and eliminate potential duplicate records and to exclude non-response and out-of-scope records.

The main type of error treated after collection is in questionnaire flow, where questions which do not apply to the respondent were found to contain answers, or conversely, where relevant questions were missed. A computer edit automatically eliminates superfluous data. All questions not included on the valid path based on previous answers are set to Valid Skip (6, 96, 996 ...). The 'Not stated' reserved codes (9, 99, 999...) are used to identify missing data resulting from issues with the computerized questionnaire or questions that are skipped because the respondent could not answer previous filter questions.

Editing is also performed at this step by modifying the data at the individual variable level, to correct for inconsistent or invalid responses.

Imputation

Imputation was done using the nearest neighbour donor imputation method. Persons that responded to all of the questions within an imputation module are considered "donor" candidates, while those with missing or invalid data are considered "recipients". A distance measure between donors and recipients is calculated based on their similarities in terms of industry (NAICS) and occupation (NOC), province, and other variables describing demographic characteristics. Data from the best possible donor are used to fill in the missing values for the recipient.

Estimation

For information on the calculation of the LFS weights, refer to the Methodology of the Canadian Labour Force Survey (Catalogue No. 71-526-X, available online).

After the calculation of the LFS final weights, further adjustments are made to derive a weight for the individual records on the CSWC microdata file:

• an adjustment to account for using only one of the six rotations in the LFS sample each month;
• an adjustment to account for sub-sampling one person per household;
• an adjustment to account for higher selection probabilities of the Indigenous and visible minority population;
• an adjustment to calibrate the weights to 18 age-sex groups, the number of employed people, four sampling quarters and broad groups of the North American Industry Classification System and the National Occupational Classification.

The calibration totals are based on final LFS estimates, which themselves are based on population projections from Statistics Canada's Demography division.

Bootstrap Weights
The bootstrap weights file provided contains 1,000 bootstrap weight replicates. In general, variance estimation using bootstrap weights is done by computing the estimate of a parameter using each set of bootstrap weights and then computing the variance of the resulting estimates. This method is valid not only for totals, means, and ratios, but also for non-linear parameters such as medians and other quantiles. These bootstrap weights can be used to compute a variety of variance estimates based on CSWC data. The bootstrap weights for the CSWC were calculated starting from the LFS bootstrap weights, and applying the same sub-sampling, non-response and calibration adjustments that were applied to create the final CSWC weights. For more information on the calculation and use of the LFS bootstrap weights, refer to the Methodology of the Canadian Labour Force Survey (Catalogue No. 71-526-X, available online).

Quality evaluation

LFS indicators were estimated using both the CSWC survey weights and the final LFS weights. Estimates were compared to verify that the CSWC weighting methodology preserved key employment totals derived from the LFS framework.

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

Two types of errors occur in surveys: sampling errors and non-sampling errors.

Sampling Errors:
Sampling errors are defined as errors resulting from the estimation of a population characteristic based on the measurement of a part of the population rather than the whole population. For probability sampling surveys, there are methods for estimating sampling errors. These methods derive directly from the sampling design and estimation method used in the survey.

The measure most often used to quantify sampling error is the sampling variance. The sampling variance indicates the extent to which the estimate of a characteristic differs from one sample to the next, given several possible samples of the same size and design. The standard error of an estimate is the square root of the sampling variance. This measure is easier to interpret, because it gives an indication of sampling error using the same scale as the estimate, whereas variance is based on squared differences.

The measure of sampling error used for the 2024-2025 CSWC is the 95% CI. A CI provides upper and lower bounds around a point estimate and indicates the degree of confidence with which the CI covers the true population value. A 95% CI of an estimate means that if the survey were repeated several times, the CI would cover the true population value 95% of the time (or 19 times out of 20). Statistics Canada's best practice is to report the sampling error of an estimate using its 95% CI.

Non-sampling Errors:
Non-sampling errors arise primarily from the following sources: non-response errors, coverage errors, measurement errors and processing errors. The response rate for the CSWC was 58.3%. Total non-response will produce a bias if non-respondents have different characteristics from respondents and if non-response is not corrected properly. Non-response adjustments and imputation helped reduce this risk of bias. Non-response to specific questions is often due to difficulty understanding the questions. Thorough quality reviews and questionnaire testing were carried out before the survey, which reduced the extent of partial non-response.

Coverage errors occur when there are differences between the target population and the sampled population (or survey population). In particular, under-coverage can be problematic. Because the CSWC sample was selected from those who had participated in the LFS, individuals who did not participate in the LFS could not be sampled for the CSWC. If this group of individuals is significantly different than the ones who participated in the LFS with respect to the characteristics measured in the LFS and CSWC, a bias could be introduced. This bias is assumed to be relatively small given the high response rate obtained in the LFS (72.9% average for CSWC months).

Measurement errors occur when an answer provided differs from the actual value. These errors may be due to respondents, the interviewer, the questionnaire, the collection method, or the data processing system. Extensive efforts were made to develop questions for the CSWC that would be understandable and relevant.

Processing errors may occur at various stages, including during the programming of the electronic questionnaire, when the interviewer or respondents enters responses, when coding, and when editing data. Quality control procedures were applied at each stage of the CSWC data processing to reduce this type of error. Data collection was conducted using an electronic questionnaire, either administered by an interviewer or self-reported by the respondent. A number of edits were built into the system to alert the respondent or interviewer to inconsistencies or unusual values, allowing for the correction of inconsistencies or errors immediately.