Nunavut Government Employee Survey (NGES)

Detailed information for 2021

Status:

Active

Frequency:

Occasional

Record number:

5226

The Nunavut Government Employee Survey (NGES) collects information from government employees about their experiences in the workplace, as well as their interest in learning, training and career advancement.

Data release - May 27, 2022

Description

The Nunavut Government Employee Survey (NGES) is an online survey of all current Government of Nunavut (GN) and Government of Canada (GoC) employees working in Nunavut. The survey is conducted by Statistics Canada, and is sponsored by Crown-Indigenous Relations and Northern Affairs Canada (CIRNAC) and Employment and Social Development Canada (ESDC). It was jointly developed by, Nunavut Tunngavik Incorporated (NTI), the GN and the GoC.

The NGES allowsemployees to share their experiences and opinions on many issues related to their workplace, learning opportunities, training and career advancement. The results of the survey will allow the Government of Nunavut and the Government of Canada to identify what is working well in each department and where improvements should be made. The results may help governments and Inuit organizations to develop and monitor Inuit Employment Plans, Pre-employment Training Plans to increase Inuit employment and support the advancement of Inuit working for government organizations in Nunavut.

The information will be used for the Nunavut Inuit Labour Force Analysis (NILFA), and may also be used to help governments and Inuit organizations to find ways to increase Inuit employee hiresin government to levels that are representative of the population, as per Article 23 of the Nunavut Agreement.

Subjects

  • Government
  • Labour

Data sources and methodology

Target population

The target population included all employees of the Government of Nunavut or the Government of Canada working in Nunavut during the reference period from April 6 to June 1st 2021. This means all indeterminate, term, contract, seasonal, student, casual employees and relief workers and substitute teachers who were working at any time during the reference period.

The survey population for the Government of Nunavut was identified from lists of employees provided by the Nunavut Bureau of Statistics. For the Government of Canada, administrative files were used and updated from lists received directly from various Government of Canada departments.

Instrument design

The 2021 NGES questionnaire was developed in collaboration with Nunavut Tunngavik Incorporated (NTI), the GN and Pilimmaksaivik, the Federal Centre for Excellence for Inuit Employment in Nunavut, Employment and Social Development Canada and Statistics Canada. Survey questions were developed to report on respondents' experience as government employees, more specifically Inuit employees working in Nunavut. This questionnaire was tested with GN employees in Iqaluit. It was also tested on GN and GoC networks before collection started.

This electronic questionnaire could be completed by employees in English, French, Inuktitut or in Inuinnaqtun.

Sampling

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

Sampling Unit
NGES is a census of Government of Nunavut employees and Government of Canada employees working in NunavutTherefore the sampling unit is a person.

Data sources

Data collection for this reference period: 2021-04-06 to 2021-08-08

Responding to this survey is voluntary.

Data are collected directly from survey respondents and extracted from administrative files.

The data collection period for Nunavut Government Employee Survey 2021 was between April 06, 2021 and August 10, 2021. The original survey closing date was initially extended by six weeksto June 30th. End of collection was then extended to July 30th and finally to August 10th to allow for some non-response follow-up (NRFU) with Government of Nunavut employees The collection method was by electronic questionnaire, provided in English, French,Inuktitut and Inuinnaqtun. During the collection period, regular e-mail reminders were sent to those who had not yet responded to the survey e-mail.

The Government of Canada and the Government of Nunavut provided Statistics Canada with employee e-mail addresses that were used to send e-mail invitations to complete the survey. Only employees with a valid e-mail address received an e-mail invitation. The invitation contained a link to the questionnaire along with a unique code to access the survey.

As soon as the respondent submitted their completed questionnaire, the data was transferred through Statistics Canada's internal network and then decrypted for processing. Respondents also had the option of saving their partially completed questionnaires to complete at a later time.

The NGES obtained administrative data under the authority of the Statistics Act from the Government of Nunavut in the form of Human Resources files. Employee names, work e-mail addresses, and information about location of work were required in order to build the survey frame and support data collected in the questionnaire.

The Government of Canada files were obtained under the authority of the Statistics Act from the Treasury Board Secretariat in the form of the Public Works and Government Services Canada Central Payroll Systems File e-mail.

Respondents were advised by Statistics Canada that their survey data may be linked to information from the Government of Nunavut and Government of Canada Human Resource administrative files for the purposes of enhancing survey data and reducing respondent burden.

Data integration was conducted on a case-by case basis. In some instances, frame variables from administrative sources were inconsistent with survey responses. In these situations, survey responses were considered to be the most accurate information and estimates were produced based on the survey responses.

The Government of Nunavut and Government of Canada Human Resources files were used for some imputation (as outlined below in the section on imputation) and to create some derived variables.

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

Error detection

Responses to the NGES were captured directly by the interviewer at the time of the interview using a computerized questionnaire. In many cases when a particular response appeared to be inconsistent with previous answers or outside of expected values, the interviewer was prompted, through message screens on the computer, to confirm answers with the respondent, and, if needed, to modify the information directly at the time of interview. This editing, however, was conducted only with errors that were fairly simple and straightforward to detect and fix. These edits were applied at the micro level.

The collected data were then subjected to further editing processes in order to correct errors that required more complex edit rules. Customized edits consisted of validity checks within and across variables to identify gaps, inconsistencies, and other problems in the data, and corrections were performed based on logical edit rules. Editing at this stage was also applied at the micro level, using SAS (Statistical Analysis System).

Imputation

Some information on the frame file was also obtained on the survey questionnaire. In these cases, the survey responses were considered to be the most accurate. If the information was missing from the survey response, some imputation was conducted to replace the non-response on the survey file using information from the survey frame. Overall, 14 missing values were imputed from matching values on the frame file.

Estimation

The NGES is a census rather than a sample. If all units had a work e-mail address available and if the response rate to the survey had been 100%, the weight would have been one for each respondent. However, not all units had a work e-mail address and not all units with a work e-mail address responded to the survey. For this reason, the survey weights were adjusted to account for both types of sample loss (non-contact due to not having an e-mail address and non-response).

The weight adjustment for non-contact consisted of inflating the weights of the units having an e-mail address to represent those for whom an e-mail address was not available. Similarly, the weights of respondents were inflated to represent the individuals who didn't respond to the survey. The adjustment factors for non-contact and non-response were calculated within non-contact and non-response weighting classes respectively, and formed using auxiliary variables available on the frame such as department, employee group type, NOC code, , region, etc. Finally, a calibration strategy was applied to the weights ,so that the sum of the weights equaled department totals and employment type.

An accurate estimation of the variance must take into account the sample loss due to non-contact and to non-response. For NGES, a generalized bootstrap method was applied to generate bootstrap weights which can be used to calculate the variance of the estimates produced.

Quality evaluation

Data validation was conducted by the subject matter team in the Centre for Indigenous Statistics and Partnerships at Statistics Canada through the verification of survey responses against expected trends and outputs.

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.

In the context of the NGES , a series of measures were implemented to prevent disclosure of confidential data. A minimum unweighted count of 10 respondents is required in every cell of any given cross-tabulation; any estimate based on fewer than 10 respondents must be suppressed or combined with other categories. For a bivariate statistic, both contributing variables must have at least this minimum number of observations to contribute, for example, both the numerator and denominator of a ratio must be based on at least 10 observations.

Another measure to protect confidential data is the prohibition of releasing unweighted data. All data must be released only in aggregate form.

For the NGES all cells in a statistical table are rounded to the nearest 10. The same procedure is used for the marginal sub-totals and totals as well as for the sums and differences of aggregates. It is recommended that researchersfollow the same guidelines related to this topic.

Revisions and seasonal adjustment

This methodology does not apply to this survey program.

Data accuracy

This survey is a census and therefore, there is no error due to sampling. However, it is subject to non-sampling errors, such as non-response and coverage errors, which can induce bias and increase sampling variance.

The frame was created using administrative files and lists of employees. Staff changes between fiscal years could impact the quality of the frame.To take into account staff changes, updates of the administrative files were performed during collection to remove units that were not part of the target population. . A total of 60 units were identified as out-of-scope for the survey, based on their survey responses. They were treated as respondents and removed after the weighting phase.

The proportion of individuals on the NGES frame with an e-mail address was 69.3% for the Government of Nunavut (GN) and 91.2% for the Government of Canada (GOC). Among the units with an e-mail address, the NGES reached a final response rate of 33.0%.

A measure for the reliability of the estimations can be the value of the associated coefficient of variation (CV). The extent of the survey error is approximated by the CV with the following guidelines:

-a CV value of 16.5% and below is considered acceptable
-a value of CV between 16.6% and 33.3% is considered marginal and requires cautionary use
-a CV value of 33.3% and above is considered too unreliable to be published.

Documentation

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