Federal Jurisdiction Workplace Survey (FJWS)

Detailed information for 2015





Record number:


The purpose of the Federal Jurisdiction Workplace Survey is to produce statistical information on the characteristics of workplaces under federal labour jurisdiction.

Data release - November 30, 2016


The purpose of the Federal Jurisdiction Workplace Survey is to produce statistical information on the characteristics of workplaces under federal labour jurisdiction. The data will be used by Employment and Social Development Canada for policy research and development.

Reference period: Calendar year

Collection period: February to June 2016


  • Hours of work and work arrangements
  • Industries
  • Labour
  • Wages, salaries and other earnings
  • Workplace organization, innovation, performance

Data sources and methodology

Target population

The target population for this survey is defined in a few steps. Initially, all establishments on Statistics Canada's Business Register were included if they had at least one employee and were classified to the following industry groups defined by the North American Industry Classification System (NAICS):

Air transportation: 481110, 481214, 481215, 488111, 488119, 488190, 561612, 611510, 621912
Rail transportation: 482112, 482113, 482114
Road transportation (local): 484110, 484221, 484222, 484223, 484229
Road transportation (excluding local): 484121, 484122, 484210, 484231, 484232, 484233, 484239, 485110, 485210, 485510, 485990, 561613
Maritime transportation: 483115, 483116, 483213, 483214, 487210, 488310, 488320, 488331, 488332, 488339, 488390
Postal services and pipelines: 486110, 486210, 486910, 491110, 492110
Banks: 521110, 522111, 522112
Feed, flour, seed and grain: 311119, 311211, 311214, 311221, 411120, 418320, 419120, 493130
Telecommunications: 515110, 515120, 515210, 517111, 517112, 517210, 517410, 517910
Other: Fisheries and oceans, nuclear industry and mines, extraction (oil and gas): 211113, 212291, 541380, 541620, 541690, 541710, 911290

While these industry groups have establishments that are most likely to be under federal labour jurisdiction, there is likely a small number of units outside these groups which should also be included. For example, NAICS 541370 and 541990 were excluded from the target population for 2015. While some establishments in these industries were known to be under federal jurisdiction based on the 2009 iteration of the survey, their contribution to total employment for Canada was very small.

Establishments belonging to federal crown corporations were also added to the target population even when their NAICS codes do not belong to one of the in-scope industries. However, no other units in these additional NAICS are included beyond those identified as belonging to crown corporations since the likelihood is low that they are under federal labour jurisdiction.

In-scope establishments belonging to the same statistical company and industry group were combined into "clusters". These clusters are called industrial companies. Clusters with only one employee were then excluded for all industrial groups except "road transportation" in order to minimise respondent burden and manage survey costs.

Instrument design

The Federal Jurisdiction Workplace Survey questionnaire for 2015 was designed by the Centre for Special Business Surveys and by Employment and Social Development Canada. The questionnaire has been field-tested with potential respondents by the Questionnaire Design Resource Centre and their comments on the design and content have been incorporated.


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

For the 2015 survey, a stratified simple random sample of about 9,500 industrial companies was selected from among the 60,231 found to belong to the population. All federal Crown Corporations were incorporated into the sample, whether or not their NAICS was part of the list of in-scope industries for the survey.

For the rest of the population, a stratified sampling strategy was used with the following stratification keys:
Nine industry groups (defined by groups of NAICS codes): air transportation; rail transportation; road transportation; water transportation; postal services and pipelines; banks; feed, floor, seed and grain; telecommunications; and other.

Four company sizes defined by number of employees: 1 to 5 employees; 6 to 19; 20 to 99; and 100 or more.

Three groups indicating the likelihood of being in-scope for the survey. The in-scope industry groups are known to have companies under federal labour jurisdiction although their number was not expected to be high in many cases. Lists of businesses known to be under federal labour jurisdiction were provided by the survey sponsor to help target in-scope units during sampling. These lists were matched to units on the Statistics Canada Business Register with varying degrees of success. The match could either be a "strong" one, a "weaker" one or could simply be deemed "unlinked". The better the match, the better the likelihood of being in-scope.

An initial allocation of the sample was done at the industry group level and when the population counts were low, a census was taken to ensure employment counts of acceptable quality.

The sample allocation was later refined within the company size groups where more industrial companies were selected from among those in the larger employment size strata in order to minimize variability in the final estimates. A census was taken of all companies with 100 or more employees.

Finally, the sample was allocated further within the size groups based on the groups indicating the likelihood of being in-scope for the survey. Units with "strong" links were forced into the sample while the "weaker" and "unlinked" units were sampled at various rates. The sampling rates for the latter two designations were determined so as to minimize the variability of the estimate resulting from combining the two strata.

The sample of companies that was pre-contacted by telephone comprised 13,500 establishments.

Data sources

Data collection for this reference period: 2016-02-25 to 2016-06-13

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

Prior to the start of the collection period for the 2015 survey, all companies in the sample were pre-contacted to determine through a series of filter questions, whether they were in-scope for the survey and to identify the contact person best placed to respond to the questionnaire. Since the assessment criteria used to determine whether a company is in-scope were different for each industry group, the filter questions were specific to each industry group. The pre-contact phase was done by computer-assisted telephone interview.

The respondent was mailed or emailed a secure access code to respond to the electronic questionnaire. Telephone follow-up was done for failed edits and non-response.

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

Error detection

A series of edit rules were applied to the captured data during processing. Invalid or inconsistent data were corrected by imputing valid entries. The edit rules used included ratios, equalities and inequalities applied at the micro level during data processing.

The processing phase of the survey was for the most part concerned with applying consistency edits and validity edits to the data reported. Consistency edits ensure that data reported in one question does not contradict information reported in another question. Validity edits ensure that the data reported is valid (i.e. that percentage values reported do not exceed 100%, that values that are supposed to sum up do in fact sum up, that skip patterns are followed, etc.).


Imputation was performed to treat partial non-responses (also called item non-responses). Note that total non-responses were accounted for during the weighting process by adjusting the weight of all responding records.

A returned questionnaire was considered as a partial non-response when some variables were fully completed by a respondent, but one or more other variables were left blank and would need to be completed via imputation. Excluding instances where certain questions do not apply to some respondents, we observed that about 7.5% of the data for the various variables required imputation (median over the unit non response rates). The imputation of non-responses was performed using the nearest neighbour donor imputation procedure in the generalized system BANFF. This procedure uses a nearest neighbour approach to find, for each record requiring imputation, the valid record that is most similar to it and that will allow the imputed recipient record to pass the specified imputation edits and post edits.

Nearest neighbour donor imputation was applied when variables in a record requiring imputation (the recipient) were identified and imputed using a donor record mostly similar to the recipient record. These similar records were found by taking into account other variables that were correlated with the missing/incorrect values via the customized imputation classes and matching variables for each variable to be imputed. If nearest neighbour donors were not found for all recipients, then it was necessary to be less restrictive by changing the imputation classes and reprocessing the data. For example, similar units would be located by region rather than by province and thus more donors in each class would be available for the recipients requiring imputation. This imputation processing continued by a predetermined sequence until nearest neighbour donors were assigned to all records requiring imputation or until no nearest neighbour donors were available. Whenever the donor and recipient records were not precisely equal for the nearest neighbour variable (typically total employment) the values from the donors were prorated the recipient's value. During imputation, edits and post edits were applied to ensure that the resulting record did not violate any of the specified edits.


The estimation involves use of weights to be used alongside the variables. These weights are simply defined as the inverse of the selection probabilities within the strata. These initial weights are later adjusted to take into account total non-response. As for variance estimation, the Generalized Estimation System was used in the context of a two-phase stratified simple random sampling approach where the first phase is the original sampling mechanism and the second phase corresponds to the total non-response mechanism.

Quality evaluation

To ensure data quality, Statistics Canada took into account and applied throughout the survey process all six dimensions of data quality control, namely, the relevance, accuracy, timeliness, accessibility, interpretability and coherence of the data collected, as per its mandate.

Data validation was conducted by the Center for Special Business Projects at Statistics Canada and the Workplace information and research division of the Labour Program at Employment and Social Development Canada (ESDC).

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects which 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 survey.

Data accuracy

The data accuracy indicators used for the Federal Jurisdiction Workplace Survey are the coefficient of variation (CV) and the standard error (SE). The CV is used for estimates expressed as a number and the SE is used for estimates expressed as a percentage. The CV and SE are included adjacent to the estimates in the published tables.

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