General Social Survey - Victimization (GSS)
Detailed information for 2014 (Cycle 28: Canadians' Safety)
Every 5 years
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.
Data release - Provinces file November 23, 2015 (First in a series of releases for this reference period.); Territories file January 27, 2016 (First in a series of releases for this reference period.)
- Questionnaire(s) and reporting guide(s)
- Data sources and methodology
- Data accuracy
The main objective of the GSS on Canadians' Safety (Victimization) is to better understand how Canadians perceive crime and the justice system and to capture information on their experiences of victimization.
This survey is the only national survey of self-reported victimization and is collected in all provinces and territories. The survey allows for estimates of the numbers and characteristics of victims and criminal incidents. As not all crimes are reported to the police, the survey provides an important complement to officially recorded crime rates. It measures both crime incidents that come to the attention of the police and those that are unreported. It also helps to understand the reasons behind whether or not people report a crime to the police.
Survey results will be used by police departments, all levels of government, victim and social service agencies, community groups and researchers not only to better understand the nature and extent of victimization in Canada, but also to study Canadians' perceptions of their safety, the levels of crime in their neighbourhoods, and their attitudes toward the criminal justice system.
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.
Reference period: Calendar year
- Crime and justice
- Society and community
- Victims and victimization
Data sources and methodology
The target population for the GSS on Canadians' Safety (Victimization) is the Canadian population aged 15 and over, living in the provinces and territories. Canadians residing in institutions are not included.
In the GSS Canadians' Safety (Victimization) conducted in the provinces, all respondents are contacted and interviewed by telephone. Thus persons in households without telephones cannot be reached. In 2013, the proportion of households without any phone service was estimated at 1%.
In the territories, respondents are interviewed by telephone or face-to-face.
In 2014, a pilot survey was conducted using the Internet as a mode of data collection. For this survey, all respondents were contacted by telephone and then redirected to the electronic questionnaire.
The questionnaire was designed based on research and extensive consultations with key justice partners and data users. Qualitative testing on new content, conducted by Statistics Canada's Questionnaire Design Resource Center (QDRC), was carried out with respondents in five cities, representing four provinces. 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. Discussions on how changes would be implemented were taken in consultation with QDRC.
This is a sample survey with a cross-sectional design.
This survey uses a frame that combines landline and cellular telephone numbers from the Census and various administrative sources with Statistics Canada's 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.
The sample is based on a stratified design employing probability sampling. The stratification is done at the province/census metropolitan area (CMA) level. Information is collected from one randomly selected household member aged 15 or older, and proxy responses are not permitted.
Data collection for this reference period: 2014-01-02 to 2015-01-17
Responding to this survey is voluntary.
Data are collected directly from survey respondents.
Data were collected using CATI and EQ. Contact was made by telephone. No proxy reporting was allowed. The respondents had the choice between French and English. Interviews were approximately 45 minutes.
Tax derived files (CSDD environment).
By linking data, we are aiming to obtain better quality data for income (personal and household).
Questions relating to income show rather high non-response rates, the incomes reported by respondents are usually rough estimates. Linking allows getting such information without having to ask questions.
The information collected during the 2014 GSS was linked to the personal tax records (T1, T1FF or T4) of respondents, and tax records of all household members. Household information (address, postal code, and telephone number), respondent's information (social insurance number, surname, name, date of birth/age, sex) and information on other members of the household (surname, name, age, sex and relationship to respondent) are key variables for the linkage.
Respondents are notified of the planned linkage before and during the survey. Any respondents who object to the linkage of their data have their objections recorded, and no linkage to their tax data takes place.
View the Questionnaire(s) and reporting guide(s).
Processing used the SSPE set of generalized processing steps and utilities to allow subject matter and survey support staff to specify and run the processing of the survey in a timely fashion with high quality outputs.
It used a structured environment to monitor the processing of data ensuring best practices and harmonized business processes were followed.
Edits were performed automatically and manually at various stages of processing at macro and micro levels. They included family, consistency and flow edits. Family relationships were checked to ensure the integrity of matrix data. A series of checks was done to ensure the consistency of survey data. An example was to check the respondent age against the respondent birth date. Flow edits were used to ensure respondents followed the correct path and fix off-path situations.
Error detection was done through edits programmed into the CATI system, as well as into the CAPI system that was used to conduct some interviews in the territories.
The CATI and CAPI data capture programs allow a valid range of codes for each question and built-in edits, and automatically follow the flow of the questionnaire.
All survey records were subjected to computer edits throughout the course of the interview. The CATI and CAPI systems principally edit the flow of the questionnaire and identify out of range values. As a result, such problems can be immediately resolved with the respondent. 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. All interviewer comments were reviewed and taken into account in head office editing.
Head office edits performed the same checks as the CATI and CAPI systems as well as more detailed edits.
A similar approach to that followed in 2009 was taken for 2014. 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 7 (97 or 997, etc.) and "Refusals" were recoded as 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 "Valid Skip", i.e. 6 (96 or 996, etc.). Due to the nature of the survey, imputation was not appropriate for most items. If a response was missing to the current question, it was coded as "Not Stated," i.e., 9 (99 or 999, etc.).
However, non-response was not permitted for those items required for weighting. Values were imputed in the rare cases where information such as the sex of the respondent was missing.
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 (himself/herself and 49 others). The number of persons represented by a given respondent is usually known as the weight or weighting factor of the sampled person.
The 2014 GSS was a survey of individuals and contains two analytical files (main analytical file and incident analytical file). The microdata files from the main survey in the provinces contain questionnaire responses and associated information from 33,127 respondents. Analytical files for the survey in the territories contain responses and information from 2,040 respondents.
Three weighting factors were placed on the Main File. These three key weighting factors 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.
WGHT_ABU: This weighting factor is required to estimate the number of victimization incidents that occurred over the past 12 months within certain violent relationships, namely those with spousal/ex-spousal or partner/ex-partner violence.
The second microdata file is the Incident Analytical File. In the provinces, 7,928 records on this file contain reports of victimization incidents and in the territories the file contains 949 records. Each victimization incident experienced by a respondent of the survey is included on one of the file's records, excluding spousal/ex-spousal and partner/ex-partner violent victimization incidents which are included in the main file.
Each record of the Incident Analytical File can be thought of as representing a number of victimization incidents experienced by persons in the overall population. This number is given by the weighting factor WGHT_VIC.
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 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.
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.
Revisions and seasonal adjustment
This methodology type does not apply to this statistical program.
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.
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 produced based on the data from the 2014 GSS. 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 include imperfect coverage and non-response.
Coverage of the 2014 GSS targeted population by the new sampling frame in the ten provinces is estimated at 86%. The coverage of the LFS frame in the territories was about 92% in the Yukon, 96% in Northwest Territories and 93% in Nunavut.
Coverage errors (or imperfect coverage) arise when there are differences between the target population and the surveyed population. In the provinces, 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. In the territories, very small communities not covered by LFS for operational and cost reasons were 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 2014 GSS was 52.9% in the provinces and 58.7% in the territories. 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.
- The General Social Survey: An Overview
Last review : January 16, 2017.
- Date modified: