General Social Survey - Personal Risk (GSS)

General Social Survey - Personal Risk (GSS)
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Detailed information for 1993 (Cycle 8)

Status:

Active

Frequency:

Every 5 years

Record number:

4504

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 the level of personal risk, (i.e. the risk of accidents and criminal victimization) and examines the awareness of victim services and contact with and perceptions of the judicial system.

Data release - 1995

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 General Social Survey - Personal Risk monitors changes in the level of personal risk, (i.e. the risk of accidents and criminal victimization) and examines the awareness of victim services and contact with and perceptions of the judicial system.

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

  • Crime and justice
  • Society and community
  • Victims and victimization

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.

Respondents were contacted and interviewed by telephone. Thus persons in households without telephones could not be interviewed. However, persons living in such households represent less than 2% of the target population.

Sampling

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

Derivation of sampling variabilities for each of the estimates which could be generated from the survey would be an extremely costly procedure, and for most users, an unnecessary one. Consequently, approximate measures of sampling variability, in the form of tables, have been developed.

Variance tables for estimates were produced using each of the four weighting factors; the Adult Weight (WGHT_PER), Child Weight (WGHT_CHD), Accident Weight (WGHT_ACC) and Crime Weight (WGHT_CRI), at the Canada level. Corresponding tables for each province, the Atlantic Region, and the Prairie Region are available upon request. It should be noted that all coefficients of variation in these tables are approximate and, therefore unofficial. Estimates of actual variance for specific variables may be purchased from Statistics Canada. Use of actual variance estimates may allow users to release otherwise unreleasable estimates, i.e. estimates with coefficients of variation in the "Not for Release" range.

The Approximate Variance tables have been produced using the coefficient of variation formula based on a simple random sample. Since estimates for the General Social Survey were based on a complex sample design a factor called the Design Effect was introduced into the variance formula. The Design Effect for an estimate is the actual variance for the estimate (taking into
account the design that was used) divided by the variance that would result if the estimate had been derived from a simple random sample. The Design Effect used to produce the Approximate Variance Tables has been determined by first calculating Design Effects for a wide range of characteristics and then choosing among these a conservative value which will not give a false impression of high precision.


In order to provide variability estimates for quantitative type variables, special tables would have to be produced. Since the variables on the General Social Survey microdata file are primarily qualitative in nature, this has not been done. 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 not be.

Data sources

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

The focus content of cycle 8 is on alcohol and drug use and their relationship to accidents and criminal victimizations.

Data for Cycle 8 of the GSS were collected monthly from February 1993 to December, 1993 inclusive. The sample was evenly distributed over the 11 months to counterbalance seasonal variation in the information gathered. All of the sample was selected using the Elimination of Non-Working Banks technique.

The survey employed Random Digit Dialling (RDD), a telephone sampling method. 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 (weighted) to represent persons without telephones.

The Elimination of Non-Working Banks (ENWB) sampling technique is a method of Random Digit Dialling in which an attempt is made to identify all working banks for an area (i.e., to identify all banks with at least one household). Thus, all telephone numbers within non-working banks are eliminated from the sampling frame.

For each province, lists of telephone numbers in use were purchased from the telephone companies and lists of working banks were extracted. Each bank was assigned to a stratum within its province.

A special situation existed in Ontario and Quebec because some small areas are serviced by independent telephone companies rather than by Bell Canada. The area code prefixes for these areas were identified by matching the Bell file with a file of all area codes and prefixes. Area code prefixes from Ontario and Quebec and not on the Bell file were identified. All banks within these area code prefixes were generated and added to the sampling frame. Use of the Waksberg method (an alternate RDD method) was not possible for these areas since it requires that an accurate population estimate be available for the survey area. Such an estimate was not available for the parts of Ontario and Quebec not covered by Bell.

A random sample of telephone numbers was generated in each survey month for each stratum (from the working banks). An attempt was made to generate the entire sample of telephone numbers on the first day of interviewing. Therefore, a prediction of the ercentage of numbers dialled that would reach a household had to be made (this is known as the "hit rate"). The hit rate for February, the first survey month, was estimated using information from previous RDD surveys.

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

Error detection

All survey records were subjected to computer edits throughout the course of the interview. With CATI, built-in edits identified invalid or inconsistent information as the interview progressed. Asa result, such problems could be immediately resolved with the respondent.

The system principally edited the main questionnaire for possible flow errors, out of range values and missing values. Edits on the 8-1 were limited to a few edits for the respondent's age and sex. The CATI system implemented such edits throughout the course of the interview. If the interviewer was unable to correctly resolve the detected errors, it was possible for the interviewer to bypass the edit and forward the data to head office for resolution.

Head office edits performed the same checks as the CATI system as well as more detailed edits. Records with missing or incorrect information were assigned non-response codes and in a small number of cases corrected from other information from the respondent's questionnaire. In mostcases editing was 'bottom-up', meaning that specific related information following a question with a branching pattern was employed to ensure that the branching was correct.

With CATI, a 'Don't know' and 'Not stated' response category were required for every question. In the edits, 'Don't know' responses were treated as a 'No' response, rather than a 'Not stated'.

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 by the questions which followed or from information from other areas of the survey.

Non-response was not permitted for those items required for weighting. Values were imputed in the rare cases where any of the following were missing: age, sex, number of residential telephone lines and the type of crime (personal or household). The imputation was based on a detailed examination of the data and the consideration of any useful data such as the ages and sexes of other household members, and the interviewer's comments.

DVTEL (number of residential telephone lines) was derived from questions E5 to E11 of the Personal Risk Questionnaire (GSS 8-2). When adequate information to derive DVTEL was not obtained, it was assigned a value of one (1).

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. These are all examples of non-sampling errors.

Over a large number of observations, randomly occurring errors will have little effect on estimates derived from the survey. However, errors occurring systematically will contribute to biases in the survey estimates. Considerable time and effort was made to reduce non-sampling errors in the survey. Quality assurance measures were implemented at each step of the data collection and processing cycle to monitor the quality of the data. These measures included the use of highly skilled interviewers, extensive training of interviewers with respect to the survey procedures and questionnaire, observation of interviewers to detect problems of questionnaire design or misunderstanding of instructions, procedures to ensure that data capture errors were minimized and coding and edit quality checks to verify the processing logic.

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.

Documentation

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