General Social Survey - Giving, Volunteering and Participating (GSS GVP)

Detailed information for 2013 (Cycle 27)




Every 5 years

Record number:


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 purpose of this survey is to collect data regarding unpaid volunteer activities, charitable giving and participation. The results will help build a better understanding of these activities which can in turn be used to help develop programs and services.

Data release - January 30, 2015


This survey is the result of a partnership of federal government departments and voluntary sector organizations that includes Canadian Heritage, Health Canada, Employment and Social Development Canada, the Public Health Agency of Canada, Canada Revenue Agency, Statistics Canada, Imagine Canada, and Volunteer Canada. This survey is an important source of information on Canadian contributory behavior, including giving, volunteering and participating.

The objectives of the survey are threefold:

1) to collect national data to fill a void of information about individual contributory behaviors including volunteering, charitable giving and civic participation;

2) to provide reliable and timely data to the System of National Accounts;

3) to inform both the public and voluntary sectors in policy and program decisions that relate to the charitable and volunteer sector.

Statistical activity

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.


  • Labour
  • Society and community
  • Unpaid work
  • Volunteering and donating

Data sources and methodology

Target population

The target population for the 2013 General Social Survey is all non-institutionalized persons 15 years of age or older, living in the ten provinces of Canada.

Instrument design

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.


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

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. Due to the potential difficulties in reaching volunteers as a result of their relatively low prevalence in the population, an approach called 'rejective sampling' was chosen as part of the sample design.

Data sources

Data collection for this reference period: 2013-09-03 to 2013-12-31

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

Data were collected using CATI. First contact was made by telephone.
No proxy reporting was allowed. The respondents had the choice between French and English. The average time to complete the survey was 44 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 will allow getting such information without having to ask questions.

The information collected during the 2013 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) were key variables for the linkage.

Respondents were notified of the planned linkage before and during the survey. Any respondents who objected to the linkage of their data had their objections recorded, and no linkage to their tax data took place.

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

Error detection

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.

The CATI data capture program allowed a valid range of codes for each question and built-in edits, and automatically follows the flow of the questionnaire.

All survey records were subjected to computer edits throughout the course of the interview. The CATI system principally edited the flow of the questionnaire and identified out of range values. As a result, such problems were immediately resolved with the respondent. If the interviewer was unable to correctly resolve the detected errors, the interviewer bypassed the edit and forwarded the data to head office for resolution. All interviewer comments were reviewed and taken into account by head office editing.

Head office performed the same checks as the CATI system as well as the more detailed edits discussed previously.


In the case of the GVP, donor imputation was used to fill in missing data for some item and partial non-response.

All imputations involved donor records that were selected using a score function. For each item non-response or partial non-response record (also called a recipient record), certain characteristics were compared to those from all potential donor records. When a characteristic was the same for a donor record and the recipient record, a value was added to the score of that donor. The donor record with the highest score was deemed the "closest" donor and was chosen to fill in missing pieces of information of the non-respondent. If there was more than one donor record with the highest score, a random selection occurred.

Imputation was done in six steps. The first three steps related to imputation of variables on the Main file. The first step was to impute both personal and household income. The second step was to impute the hours volunteered by activity for the main organization. The third step was to impute the total hours volunteered for the second and third organizations and the total hours volunteered for all other organizations combined. The fourth step was to impute variables on the Giving (GS) file related to amount donated. This step also included creating additional GS file records for cases where a value for GS_Q07 was imputed as "yes". The fifth step was to impute, on the Main file, missing data in any of the variables indicating whether the respondent made a donation in response to each of the 13 methods of solicitation. At this stage, imputation was performed only for cases which were already known to be givers. This step also included creating additional GS records for cases where one or more of FG_Q03 to FG_Q15 was imputed as "yes". The sixth step was to impute partially completed records where the donor status could not be determined because of missing values in FG_Q03 to FG_Q15. A total of 88 variables were imputed. This last step again included creating additional GS file records for cases where any of FG_Q03 to FG_Q15 was imputed as "yes".

The GVP imputation process worked well and helped to fill incomplete responses with the experience of other respondents with similar or identical characteristics. This adds to the number of units used in any analysis performed by researchers.


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. Furthermore, in order to adjust for the 'rejecting' of a proportion of respondents that are not volunteers, the person weight for respondents that are not 'rejected' and are not volunteers is multiplied by a factor. Finally, the weights were adjusted so that the weighted income distribution of GVP matched the 2012 SLID distribution by province

The 2013 GSS GVP was a survey of individuals and the analytic files contain questionnaire responses and associated information from 14,714 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 evaluation

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.

The weighted income distribution of the GSS GVP was compared with the distribution of income according 2012 Survey of Labor and Income Dynamics (SLID) data. This validation exercise resulted in the adjustment of weights so that the distribution of the weighted income of the GSS GVP corresponds to the 2012 SLID distribution by province.

Estimates related to volunteering and donations were compared with those obtained during the previous iterations of the survey to evaluate the coherence and overall reasonableness of trends. Estimates were also compared to estimates from other surveys and administrative data bases on the same topics.

The estimates were also submitted to recognized external experts through an advance release procedure for purposes of data validation, in accordance with the Work in progress agreements (WIP).

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.

Revisions and seasonal adjustment

This methodology type does not apply to this statistical program.

Data accuracy

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 the 2013 GSS GVP. 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 5% level.


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