General Social Survey - Time Use (GSS)

General Social Survey - Time Use (GSS)
Summary of changes
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Detailed information for 2010 (Cycle 24)

Status:

Active

Frequency:

Every 5 years

Record number:

4503

The two primary objectives of the General Social Survey (GSS) are: to gather data on social trends in order to monitor changes in the living conditions and well-being of Canadians over time; and to provide information on specific social policy issues of current or emerging interest. A specific topic is usually repeated every five years.

This survey monitors changes in time use.

Data release - July 12, 2011

Description

The two primary objectives of the General Social Survey (GSS) are: to gather data on social trends in order to monitor changes in the living conditions and well-being of Canadians over time; and to provide information on specific social policy issues of current or emerging interest. A specific topic is usually repeated every five years.

This survey monitors changes in time use.

The data collected provide information to all level of governments when making funding decisions, developing priorities and identifying areas of concern for legislation, new policies and programs. Researchers and other users use this information to inform the general Canadian population about the changing nature of time use in Canada.

Statistical activity

This record is part of the General Social Survey (GSS) program. The GSS, originating in 1985, conducts telephone surveys. Each survey contains a core topic, focus or exploratory questions and a standard set of socio-demographic questions used for classification. More recent cycles have also included some qualitative questions, which explore opinions and perceptions.

Until 1998, the target sample of respondents was approximately 10,000 persons. This was increased in 1999 to 25,000. With a sample of respondents of 25,000, results are available at both the national and provincial levels and possibly for some special population groups such as disabled persons and seniors.

Subjects

  • Commuting to work
  • Labour
  • Society and community
  • Time use
  • Unpaid work

Data sources and methodology

Target population

The target population for the GSS on Family is the Canadian population aged 15 and over, living in the 10 provinces, and not residing in institutions.

In the GSS, all respondents are contacted by telephone. Thus persons in households without telephones cannot be interviewed. However, persons living in such households represent less than 2% of the target population.

Instrument design

The questionnaire was designed based on qualitative testing (focus groups), a pilot test and interviewer debriefing.

Sampling

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

In the ten provinces, households will be selected for the survey by Random Digit Dialing. The telephone numbers in the sample are selected using the Elimination of Non-Working Banks technique. This sampling technique is a method in which an attempt is made to identify all working banks for an area (i.e., to identify all sets of 100 telephone numbers with the same first eight digits containing at least one number that belongs to a household). Thus, all telephone numbers within non working banks are eliminated from the sampling frame.

Each of the ten provinces is divided into strata, i.e. geographic areas. Many of the Census Metropolitan Areas (CMAs) are each considered separate strata: St. John's, Halifax, Saint John, Montreal, Quebec City, Toronto, Ottawa, Hamilton, Winnipeg, Regina, Saskatoon, Calgary, Edmonton, Vancouver and Victoria. CMAs not on this list are located in Quebec and Ontario, and two more strata are formed by grouping the remaining CMAs in each of these two provinces. Finally, the non-CMA areas of each of the ten provinces are also grouped to form ten more strata. This gives a total of 27 strata for the provinces.

Data sources

Data collection for this reference period: 2010-01-04 to 2010-12-31

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

Data collection was conducted by Computer Assisted Telephone Interviewing (CATI) methods in the 10 provinces.

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

Error detection

Error detection is done through edits programmed into the CATI system.

The CATI data capture program allows a valid range of codes for each question and built-in edits, and automatically follows the flow of the questionnaire.

All survey records are subjected to computer edits throughout the course of the interview. The CATI system principally edits the flow of the questionnaire and identifies out of range values. As a result, such problems can be immediately resolved with the respondent. If the interviewer is unable to correctly resolve the detected errors, it is possible for the interviewer to bypass the edit and forward the data to head office for resolution. All interviewer comments are reviewed and taken into account in head office editing.

Head office edits perform the same checks as the CATI system as well as more detailed edits.

Imputation

The flow editing carried out by head office followed a 'top down' strategy, in that whether or not a given question was considered "on path" was based on the response codes to the previous questions. If the response codes to the previous questions indicated that the current question was "on path", the responses, if any, to the current question were retained, though "don't know" was recoded as 9 (99 or 999, etc.) and refusals were recoded as "Not Stated", i.e. 8 (98 or 998, etc.). If the response codes to the previous questions indicated that the current question was "off path" because the respondent was clearly identified as belonging to a sub-population for which the current question was inappropriate or not of interest, the current question was coded as "Not Asked", i.e. 7 (97 or 997, etc.).

Due to the nature of the survey, imputation was not appropriate for most items so missing data were coded as 'Not stated'.

However, non-response was not permitted for those items required for weighting. Values were imputed in the rare cases where either of the following was missing: sex or number of residential telephones.

Estimation

When a probability sample is used, as is the case for the GSS, the principle behind estimation is that each person selected in the sample represents (in addition to himself/herself) several other persons not in the sample. For example, in a simple random sample of 2% of the population, each person in the sample represents 50 persons in the population. The number of persons represented by a given person in the sample is usually known as the weight or weighting factor of the sampled person.

GSS Cycle 24 estimates can be produced from two microdata files, the main analytical file and the episode file. The main file contains questionnaire responses and associated information from 15,390 respondents and the episode file provides the detailed information on each activity episode reported by respondents.

Four weighting factors were placed on the Main File. They are listed and explained below:

WGHT_PER: This is the basic weighting factor for analysis at the person level, i.e. to calculate estimates of the number of persons (non-institutionalized and aged 15 or over) having one or several given characteristics. WGHT_PER should be used for all person-level estimates.

WGHT_HSD: This weighting factor can be used to estimate the number of households with a given characteristic.

In addition, respondents were split (randomly) into two approximately equal sub-samples for Section 9 of the questionnaire. Half of the respondents were asked the questions in the Cultural Activities module and the other half were asked the questions in the Sports Participation Activities, Sports Participation of Partner and Sports Participation of Household Children modules. As a result of splitting the sample, the following sets of weights were created.

WGHT_CSP: This is the weighting factor for analysis at the person level created using the sample of persons asked the questions in the Cultural Activities module. This weight is zero for respondents who completed the Sports Participation Activities modules.

WGHT_SNT: This is the weighting factor for analysis at the person level created using the sample of persons asked the questions in Sports Participation Activities module. This weight is zero for respondents who completed the Cultural Activities module.

The second microdata file is the Episode File. The Episode File consists of 283,287 records. Each record represents a single activity in a respondent's day, and all respondent's episodes must add up to twenty four hours (1440 minutes). The WGHT_EPI indicates the number of time use episodes that a record on the Episode File represents.

In addition to the estimation weights, bootstrap weights have been created for the purpose of design-based variance estimation.

Quality evaluation

Quality assurance measures were implemented at every collection and processing step. Measures included recruitment of qualified interviewers, training provided to interviewers for specific survey concepts and procedures, observations of interviews to correct questionnaire design problems and instruction misinterpretations, procedures to ensure that data capture errors were minimized and edit quality checks to verify the processing logic. Data are verified to ensure internal consistency and they are also compared to other published sources.

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 order to prevent any data disclosure, confidentiality analysis is done using the Statistics Canada Generalized Disclosure Control System (G-Confid). G-Confid is used for primary suppression (direct disclosure) as well as for secondary suppression (residual disclosure). Direct disclosure occurs when the value in a tabulation cell is composed of or dominated by few enterprises while residual disclosure occurs when confidential information can be derived indirectly by piecing together information from different sources or data series.

Revisions and seasonal adjustment

This methodology does not apply to this survey.

Data accuracy

The methodology of this survey has been designed to control errors and to reduce the potential effects of these. However, the results of the survey remain subject to error due to both sampling error and non-sampling error.

Sampling error:
As the data are based on a sample of persons they are subject to sampling error. That is, estimates based on a sample will vary from sample to sample, and typically they will be different from the results that would have been obtained from a complete census. The potential range of this difference has been estimated for key data and used to produce tables that can be used to estimate the sampling variability of many estimates. More precise estimates of the sampling variability of estimates can be produced with the bootstrap method using bootstrap weights that have been created for this survey. Estimates with high sampling variability are indicated in this publication and all of the highlighted differences between subgroups of the population are significant at the 95% level.

Non-sampling error:
Even a census of the population of interest produces estimates subject to error. While these are called non-sampling errors, estimates from samples still contain errors of this type. Common sources of these errors are imperfect coverage, non-response, response errors, and processing errors.

Coverage of the GSS-24 targeted population by the RDD frame is estimated to be more than 86% complete; rates of telephone service are very high in Canada. These rates are high for virtually all socio-demographic groups, but are lowest among those households with the lowest incomes. As a result persons living in such households are slightly under-represented in the GSS-24 sample. In addition, while every effort was made to avoid non-response, the non-response rate for GSS-24 was 45%. Little or nothing is known about the non-responding cases, and so the results may be biased to the extent that the non-responding cases differ from those that provided responses.

Documentation

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