General Social Survey - Time Use (GSS)

Status:
Active
Frequency:
Quinquennial (5 year)
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.

This survey monitors changes in Time Use.

Detailed information for 1998 (Cycle 12)

Data release - November 9, 1999

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.

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

Data sources and methodology

Target population

The target population includes all persons 15 years of age and older in Canada, excluding:
1. Residents of the Yukon, Northwest Territories, and Nunavut
2. Full-time residents of institutions.

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 survey, all respondents were contacted by telephone. Households without telephones were therefore excluded; however, persons living in such households represent less than 2% of the target population. Survey estimates have been adjusted (i.e., weighted) to account for persons without telephones. The tacit assumption is that, given the small number of people without telephones, their characteristics are not different enough from those of the rest of the target population to have an impact on the estimates. Since no one without a telephone is in the sample, this assumption cannot be verified using GSS data. The characteristics of the population without telephones has been examined using data from the Survey of Consumer Finance and the Household Facilities and Equipment Survey. Telephone ownership is high among virtually all socio-economic groups, but is lowest among the 3% of the population with the lowest household income (less than $10,000). The telephone ownership rate was 92.6% for this population, while it was over 96% for all other groups.

The GSS used a stratified design, with significant differences in sampling fractions between strata. Thus, some areas are over-represented in the sample (relative to their populations) while some other areas are relatively under-represented; this means that the unweighted sample is not representative of the target population, even if there were no non-response.

Since it is an unavoidable fact that estimates from a sample survey are subject to sampling error, sound statistical practice calls for researchers to provide users with some indication of the magnitude of this sampling error.

Although the exact sampling error of the estimate, as defined above, cannot be measured from sample results alone, it is possible to estimate a statistical measure of sampling error, the standard error, from the sample data. Using the standard error, confidence intervals for estimates (ignoring the effects of non- sampling error) may be obtained under the assumption that the estimates are normally distributed about the true population value. The chances are about 68 out of 100 that the difference between a sample estimate and the true population value would be less than one standard error, about 95 out of 100 that the difference would be less than two standard errors, and virtually with certainty that the differences would be less than three standard errors.

Data sources

Data collection for this reference period: February 1998 to December 1998

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

As in the other General Social Surveys taken since 1994, data for Cycle 12 were collected using Computer Assisted Telephone Interviewing (CATI) using Computer-Assisted Survey Execution System software (CASES). With CATI, the survey questions appeared on a computer monitor. The interviewer asked the respondent the questions, and entered the responses into the computer as the interview progressed. CATI methodology eliminated the need for paper and pencil questionnaires.

Cycle 12 was the third cycle (the first two were Cycles 2 and 7) to collect data on time use. It included additional questions on activities helping someone. The data enabled analysts to measure unpaid work, such as time spent looking after children or elderly persons, volunteer work, time crunch and quality of life. With funding from Sports Canada and other cultural agencies and departments, participation in sports and cultural activities was also included in this cycle. For the first time, respondents were asked questions about satisfaction and life cycles.

All interviewing took place using centralized telephone facilities in four of Statistics Canada's regional offices with calls being made from 9:00 until 21:00, Monday to Friday inclusive, and from 12:00 until 16:00 on Saturday and Sunday. The four regional offices were: Halifax, Montreal, Winnipeg and Vancouver. Interviewers were trained by Statistics Canada staff in telephone interviewing techniques using CATI, survey concepts and procedures in a two day classroom training session. The majority of interviewers had computer and telephone interviewing experience.

Using CATI, responses to survey questions were entered directly into computers as the interview progressed. The CATI data capture program allowed a valid range of codes for each question and automatically followed the flow of the questionnaire. Certain edits were also executed by the CATI system. The data were then transmitted to Ottawa electronically.


A GSS 12-1 selection control questionnaire was completed for each telephone number generated in the sample. When a private household was contacted, all household members were enumerated and basic demographic information was collected for everyone. A computer algorithm randomly selected an eligible household member age 15 or over to answer the Time Use questionnaire. This form was also used to determine the eligible collection days for the purpose of scheduling appointments to complete the questionnaire.

Data for Cycle 12 of the GSS were collected monthly from February 1998 to January 1999 inclusive. The sample was evenly distributed over the 12 months to represent the seasonal variation in the information. The sample was selected using the Elimination of Non-Working Banks technique of Random Digit Dialing (RDD). Since people's activities also differ by the day of the week, a sample that was representative of each day of the week was required. Each telephone number was therefore assigned a 'designated day'. Cases were eligible for collection for 2 days following the designated day; with priority given to collecting diary information on the day following the designated day.

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

Error detection

During the interview, the CATI system ensured that branchings were correct and that the values were valid. In cases where the interviewer was unable to correct errors detected by the system, he/she could provide a comment and leave the problem for Head Office to solve.

The Head Office edit system performed the same kind of checks as the CATI system, as well as verifications of greater complexity. The flow of the responses through the various paths in the questionnaire were verified.

The data items used for weighting, such as age, sex and number of telephone lines, needed to have values for all respondents. In the case of the age variable, the procedure used to select the respondent ensured that a response would be present. By contrast, values were imputed in the rare cases where the number of residential telephone lines was missing. The number of residential telephone lines was assumed to be one (1) when the respondent failed to provide the information.

Due to the nature of the survey, imputation was not appropriate for most items and thus 'not stated' codes were usually assigned for missing data. In some cases, the answer was not known but could be obtained deterministically from other information on the survey.

Errors which are not related to sampling may occur at almost every phase of a survey operation. Interviewers may misunderstand instructions, respondents may make errors in answering questions, the answers may be incorrectly entered on the questionnaire and errors may be introduced in the processing and tabulation of the data.

Estimation

Statistics from the General Social Survey (GSS) databases are estimates based on data collected from a small fraction of the population (roughly one person in 2,000) and are subject to error. The error can be divided into two components: sampling error and non-sampling error.

Sampling error is the difference between the estimate derived from a sample and the result that would have been obtained from a population census using the same data collection procedures. For a sample survey such as the GSS, this error is estimated from the survey data. The measurement of error used is the standard deviation of the estimate. When a sampling error is more than 33 1/3% of the estimate itself, it is considered to be too unreliable to be published. In such a case, the symbol ' -- ' appears in statistical tables in place of the estimate. When the sampling error is between 16 2/3% and 33 1/3%, the corresponding estimate is accompanied by the symbol " * ' in a table. Such estimates should be used with caution. Finally, all estimates with a sampling error of less than 16 2/3% can be used without restriction.


All other types of errors, such as coverage, response, processing, and non-response, are non-sampling errors.

Many of these errors are difficult to identify and quantify.

Coverage errors arise when there are differences between the target population and the surveyed population. Households without telephones represent a part of the target population that was excluded from the surveyed population. To the extent that this excluded population differs from the rest of the target population, the estimates will be biased. Since these exclusions are small, one would expect the biases introduced to be small. However, since there are correlations between a number of questions asked on this survey and the groups excluded, the biases may be more significant than the small size of the groups would suggest.

Individuals residing in institutions were excluded from the surveyed population. The effect of this exclusion is greatest for people aged 65 and over, for whom it approaches 9%.

In a similar way, to the extent that the non-responding households and persons differ from the rest of the sample, the estimates will be biased. The overall response rate for the GSS was approximately 80%. Non-response could occur at several stages in this survey. There were two stages of information collection: at the household level and at the individual level. Non-response at the household level averaged 6%. Non-response also occurs at the level of individual questions. For most questions, the response rate was high and, in tables, the non-responses generally appear under the heading "not stated".

While refusal to answer specific questions was very low, accuracy of recall and ability to answer some questions completely can be expected to affect some of the results presented in the subsequent chapters. Awareness of exact question wording will help the reader interpret the survey results.

Since the survey is cross-sectional, caution is required in making causal inferences about the association between variables. Observed associations may be a reflection of differences between cohorts, period effects, differences between age groups or a combination of these factors.

When a probability sample is used, as was 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.

There are two microdata files from which GSS Cycle 12 estimates can be made. The Main File contains summary time use information from 10,749 respondents. It also contains the questionnaire

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 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.

Data accuracy

Approximate variances for quantitative variables cannot be as conveniently summarized. As a general rule, however, the coefficient of variation of a quantitative total will be larger than the coefficient of variation of the corresponding qualitative estimate (e.g., the number of persons contributing to the quantitative estimate). If the corresponding qualitative estimate is not releasable, then the quantitative total will in general not be releasable.

Before releasing and/or publishing any estimates from the microdata file, users should consider whether or not to release the estimate based on the following guidelines:

1.Moderate sampling variability (c.v. 0.0 to 16.5%) - Estimates can be considered for general unrestricted release. No special notation is required.

2. High sampling variability (16.6 to 33.3%) - Estimates can be considered for general unrestricted release but should be accompanied by a warning cautioning users of the high sampling variability associated with the estimates.

3. Very high sampling variability (c.v. 33.4% or over) - Estimates should generally not be released, but when they are it should be with great caution and the very high sampling variability associated with the estimate should be prominently noted.

Note: The sampling variability policy should be applied to rounded estimates.

Users should determine the number of records on the particular microdata file which contribute to the calculation of a given estimate. This number should be 15 or more. When the number of contributors to the weighted estimate is less than this, the weighted estimate should not be released regardless of the value of the Approximate Coefficient of Variation.

Data file