General Social Survey - Social Identity (SI)
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.
The main objective of the GSS on Social Identity (SI) is to provide an overall picture of Canadians' identification, attachment, belonging and pride in their social and cultural environment.
Detailed information for 2013 (Cycle 27)
Data release - December 23, 2014
The key components of the survey include the following topics:
- Social networks, civic participation and engagement, knowledge of Canadian history, appreciation of national symbols, shared values, confidence in institutions and trust in people.
Results from this survey will be used by analysts and researchers to study the relationship between identity and social integration, and by government departments to develop policies and programs.
In addition, the GSS on Social Identity is a multi-mode survey. Respondents selected for the SI questionnaire will be given two options for responding: completing the electronic questionnaire (EQ) or continuing the computer-assisted telephone interview (CATI).
This record is part of the General Social Survey (GSS) program. The GSS originated in 1985. 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.
- Social networks and civic participation
- Society and community
Data sources and methodology
The target population for the main 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.
The questionnaire was designed based on research and extensive consultations with data users. Qualitative testing, conducted by Statistics Canada's Questionnaire Design Resource Center (QDRC), was carried out, with respondents in four cities, representing three provinces, who were screened in based on representative criteria. Questions which worked well and others that needed clarification or redesign were highlighted. QDRC staff compiled a detailed report of the results along with their recommendations. All comments and feedback from qualitative testing were carefully considered and incorporated into the survey when possible.
The pilot test of the data collection methodology and questionnaire was conducted from October to December 2012. Data collection observations of the pilot test were conducted by survey team members. All observation comments and suggestions were fully documented and, along with comments from interviewers, analyzed and implemented into the survey when possible.
This is a sample survey with a cross-sectional design.
The target sample size (i.e. the number of respondents) for Cycle 27 SI was 31,973, while the actual number of respondents was 27,695. For each province, minimum sample sizes were determined that would ensure certain estimates would have acceptable sampling variability at the stratum level. Once these stratum sample size targets had been met, the remaining sample was allocated to the strata in a way that balanced the need for precision of both national-level and stratum-level estimates.This sample was representative of all households in Canada.
In order to carry out sampling, the ten provinces of the target population are divided into strata (i.e. geographic areas). Many of the Census Metropolitan Areas (CMAs) are each considered separate strata. This was the case for St. John's, Halifax, Saint John, Montreal, Quebec City, Toronto, Ottawa (Ontario part of Ottawa - Gatineau CMA), Hamilton, Winnipeg, Regina, Saskatoon, Calgary, Edmonton, Vancouver and Victoria. CMAs not on this list are located in New Brunswick, Quebec, Ontario and British Columbia. For Quebec, Ontario and British Columbia, three more strata were formed by grouping the remaining CMAs in each of these three provinces (Québec part of Ottawa - Gatineau CMA of is in Quebec-Other-CMAs). Next, the non-CMA areas of each of the ten provinces were grouped to form ten more strata. Moncton is included with the non-CMA group for New Brunswick. This resulted in 27 strata in all.
This survey uses a new frame combining landline and cellular telephone numbers from the Census and various administrative sources with Statistics Canada's new dwelling frame. Records on the frame are groups of one or several telephone numbers associated with the same address (or single telephone number in the case a link between a telephone number and an address could not be established). This sampling frame is used to obtain a better coverage of households with a telephone number.
Data collection for this reference period: 2013-06-03 to 2014-03-31
Responding to this survey is voluntary.
Data are collected directly from survey respondents.
The data are collected using both a CATI application and an Electronic Questionnaire (EQ). An introduction letter and pamphlet is sent in advance to respondents for which an address is available.
View the Questionnaire(s) and reporting guide(s) .
All survey records were subjected to computer edits throughout the course of the interview. The survey application identified out of range values as they were entered. As a result, the interviewer (in CATI) or the respondent (in EQ) could immediately correct the information provided to resolve the issue. If the interviewer (or the respondent) was unable to correctly resolve the detected errors, it was possible to bypass the edit to continue the survey and the data was reviewed later by head office. All interviewer comments from the CATI system were reviewed and taken into account in head office editing.
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 the sex of the respondent was missing for example.
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 (himself/herself and 49 others). The number of persons represented by a given respondent is usually known as the weight or weighting factor.
GSS Cycle 27 was a survey of individuals and the analytic files contain questionnaire responses and associated information from 27,695 respondents.
A weighting factor is available on the microdata file:
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.
In addition to the estimation weights, bootstrap weights have been created for the purpose of design-based variance estimation.
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.
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.
For microdata: content is reduced and modified. For tabular data: sensitive cells correction methods such as cell collapsing and suppression are applied.
The methodology of this survey has been designed to limit the number of errors and to reduce their potential effects. However, the results of the survey remain subject to both sampling and non-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. 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 produced based on the data from GSS Cycle 27. 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.
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 and non-response.
Coverage errors (or imperfect coverage) arise when there are differences between the target population and the surveyed population. Households without telephones, as well as households with telephone services not covered by the current frame, represent a part of the target population that was excluded from the surveyed population. To the extent that the excluded population differs from the rest of the target population, the results may be biased. In general, since these exclusions are small, one would expect the biases introduced to be small.
The overall response rate for GSS cycle 27 was 48.1%. 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. Some non-response occurred at the household level, and some at the individual level. Survey estimates have been adjusted (i.e. weighted) to account for non-response cases. To the extent that the non-responding households and persons differ from the rest of the sample, the results may be biased.
Other types of non-sampling errors can include response errors and processing errors.
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