General Social Survey - Family (GSS)

Status:
Active
Frequency:
Quinquennial (5 year)
Record number:
4501

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 the changes in the structure of families with respect to marriages, common-law unions, children and fertility intentions.

Detailed information for 2011 (Cycle 25)

Data release - July 18, 2012

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.

This survey monitors changes in Canadian families. It collects information on: conjugal and parental history (chronology of marriages, common-law unions and children), family origins, children's home leaving, fertility intentions as well as work history and other socioeconomic characteristics.

The information collected will impact program and policy areas such as parental benefits, child care strategies, child custody and spousal support programs.

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 intentions and perceptions.

Until 1998, the target sample size was approximately 10,000 persons. For 2011, this was established at 25,000. With a sample of 25,000, results are available at both the national and provincial levels and possibly for some special population groups such as visible minorities and seniors.

Subjects

  • Families, households and housing
  • Family history
  • Family types
  • Household characteristics
  • Society and community

Data sources and methodology

Target population

The target population for the GSS is all non-institutionalized persons 15 years of age or older, living in the ten provinces of Canada.

In the GSS, all respondents are contacted and interviewed 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 (one on one interviews), a pilot test and interviewer debriefing.

The pilot test (with a sample size of approximately 400 households) of the data collection methodology and questionnaire was conducted in July 2010.

Sampling

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

Households were selected for the survey by Random Digit Dialing. The telephone numbers in the sample were 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 numbers within non-working banks are eliminated from the sampling frame.

In order to carry out sampling, each of the ten provinces was divided into strata, i.e. geographic areas.

Many of the Census Metropolitan Areas (CMAs) were each considered separate strata. This was the case for St. John's, Halifax, Saint John, Montreal, Quebec City, Toronto, Ottawa, Hamilton, Winnipeg, Regina, Saskatoon, Calgary, Edmonton and Vancouver. CMAs not on this list are located in Quebec, Ontario and British Columbia. Three more strata were formed by grouping together the remaining CMAs in each of these three provinces. Finally, the non-CMA areas of each of the ten provinces formed ten more strata. This resulted in 27 strata in all.

Data sources

Data collection for this reference period: 2011-02-01 to 2011-11-30

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 a population of 1000 people, 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.

The estimates for GSS Cycle 25 can be obtained from the microdata file which contains questionnaire responses and associated information from 22,435 respondents.

Two 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_HSD: This is the usual GSS household weight, to be used only for estimate of household characteristics. For example, to estimate the number of households that live in low-rise apartments, WGHT_HSD should be summed over all records with this characteristic.

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 steps. Measures such as 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 captures are minimized and edit quality checks to verify the processing logics. Data are verified to ensure internal consistency and they are also compared to previous survey results to ensure historical continuity.

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

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. The bootstrap method was used to estimate the sampling variability for all of the estimates included in the publication series 'General Social Survey, Cycle 25: Families. Estimates with high sampling variability are indicated in the publications 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-25 targeted population by the RDD frame is estimated to be approximately 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-25 sample. In addition, while every effort was made to avoid non-response, the non-response rate for GSS-25 was 34%. 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.