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« Chapter 3 - Introduction »

Integrating a gender perspective into data collection goes beyond recording the sex of the respondent (or household member, reference person or head of the household, for that matter). It entails a review of the data collection process in all its stages – the selection of topics to be covered by the survey or census, questionnaire or form design, sample design, selection and training of interviewers and supervisors, data collection in the field, data coding and data editing – and paying attention to all factors that could potentially lead to a gender bias in the data.

  • + General model for integrating a gender perspective into censuses and surveys
    • Setting out the objectives of surveys or censuses

      The integration of a gender perspective into data collection should be taken into account from the stage of planning the data collection and setting out the objectives of the survey or census. Usually, the objectives of a survey or census are based on several factors: topics and policy issues that need to be addressed, review of previous data collections within the same programme, information available from other data sources, international statistical standards; a country’s institutional capacity for collecting data and financial and other resources available. It is important that a gender perspective be incorporated into the review of previous data collections, in terms of both topics covered and the specific implementation, as reflected in data collection instruments and materials. National statistical offices can use their plan for the production of gender statistics to decide what gender statistics are to be collected by the particular survey or census developed at the time and what is to be covered by other sources of data. It is also important for gender specialists to be involved in the process of developing data collection objectives. This process is typically based on extensive consultations between data producers and data users such as technical experts, data analysts, researchers, policy analysts and policymakers. Both gender statisticians and gender specialists representing the point of view of data users and policymakers should be part of the team.

      Questionnaire design and testing

      Within the topics agreed to be covered by the survey or census, relevant gender issues should be identified and gender-specific conceptual and measurement issues should be taken into account (as discussed in chapter II). These elements should be reflected in the questionnaire design, the interviewer’s manual and the training of the interviewers and supervisors.

      The questionnaire design should ensure that gender-specific conceptual and measurement issues are adequately reflected in the questions. The design should benefit from consultations with a wide range of specialists, such as subject matter specialists, classification and coding experts, field supervisors, data processing staff and data analysts. It is important that members of the team designing the questionnaire are knowledgeable of gender issues.

      The language, terms or phrasing of the questions should not induce gender biases. In particular, the following guidelines are recommended:

      (a) The questionnaire should contain very short explanatory notes for the interviewer when needed, with more elaborate instructions, explanations of terms or, in some cases, definitions and key concepts provided in the interviewer’s manual;

      (b) Probing questions should be used in order to reduce underreporting related to women, both to help respondents remember something that they may have forgotten and to help interviewers properly code the answers to some questions;

      (c) Questions should be written out in detail, with the reference period clearly specified. In some cases it may also be helpful to give examples of responses or the complete list of categories of answers;

      (d) Potential answers to questions should be categorized and pre-coded in such a way that answers related mainly to women are given the same importance as those mainly related to men;

      (e) Questions should be kept as short and simple as possible, free from ambiguity, and use common everyday terms, so that all respondents, regardless of their educational level, have no difficulty understanding them;

      (f) Questions should not influence answers or be leading. Keywords in the questions should not apply exclusively to only one of the two sexes (for example, “housewife” or “fisherman”) and they should maintain their meaning when translated into major languages of a country.

      The questionnaire should be field-tested to ensure that both women and men understand the questions in the same way and to detect potential underreporting or other bias related to either women or men.


      Gender-related measurement issues and gender stereotypes should be addressed in the manuals for interviewers and supervisors. Manuals should have detailed explanations on questions that may lead to underreporting or sex-selective underreporting (for example, domestic violence or economic activity); instructions and examples on how to use probing questions or lists (for example, in measuring economic activity); and, where applicable, instructions on how to code the answers (for example, in measuring self-employment or detailed marital status). The general language should be free of gender-based biases or other stereotypes related to the characteristics measured, and the examples given should not reinforce gender stereotypes.


      Samples used should cover all groups of population, households, agricultural holdings or economic units known to have distinct gender patterns. The sample design should also ensure that reliable statistics are produced for both women and men in sufficient detail and allow disaggregation by other characteristics as required for meaningful gender analysis. For example, the sample of a survey measuring status in employment should be large enough to allow for the data to be analysed according to female and male groups of employers or any other categories of self-employed, as well as further disaggregated by age group, rural/urban areas and educational attainment.

      Selection and training of interviewers and supervisors

      The selection and training of interviewers and supervisors are important elements in obtaining reliable gender statistics. Gender-related measurement issues and gender stereotypes should be addressed in the training for interviewers and supervisors. For example, the training should cover situations in which multiple respondents within the household need to be interviewed to avoid indirect reporting (for instance, in recording literacy) or when information needs to be collected from household members that are most knowledgeable of the issue (for instance, household food consumption or number of children ever born). The training should also include how to handle the interview environment when sensitive questions need to be asked, such as in the case of violence against women, or even in the case of women’s earnings. In addition, training should emphasize understanding of general gender issues related to the topics covered by the survey or census and how the data collected will address those issues, so that interviewers and supervisors can cope with issues and problems not specifically addressed in the manuals or training.

      It is important that the field staff be selected on the basis of competence, and that both women and men be recruited as interviewers or supervisors. Certain types of surveys – such as violence against women surveys – need more careful selection and more extensive training of interviewers. The sex of the interviewer often plays an important part in obtaining certain types of information from the respondents. Women, for example, are more likely to disclose information on sensitive topics such as violence against women or reproductive health to women interviewers than to men interviewers.

      Data coding and data editing

      It is important that gender bias not be introduced into the data at the stage of data coding and data editing. Data coding and data editing are data transformations that improve internal consistency and the conceptual soundness of data. Whenever possible, pre-coded responses are used in the questionnaires, and some of the data coding can be done by the interviewers directly in the field by coding the respondent’s answer into the questionnaire. Other coding needs to be done by specialized coders using code books or computer programs, and some of the data errors may need to be fixed through data imputation. It is important that classification and subject matter specialists with training in gender issues be involved in formulating rules for data coding, data editing and data imputation, so that assumptions based on gender stereotypes are avoided.

  • + Organization and use of the chapter
    • The issues described above are general issues that need to be taken into account when mainstreaming gender into data collection; however, depending on the type of data collection, more specific issues will need to be considered. The sections that follow provide guidance on bringing a gender perspective into three major data collection vehicles that yield gender statistics: population and housing censuses, agricultural censuses and surveys and labour force surveys. Time-use surveys and violence against women surveys are also presented but are covered here in less detail, as complete and recent manuals have been dedicated to the topic of these gender-focused data collections.5 For each of the three sources of data, the chapter addresses the types of topics usually covered in data collection, their relevance for gender statistics and the practices used to improve, from a gender perspective, the data collection.

      The information in this chapter can be used to take into account gender issues and gender biases in measurement when designing or redesigning surveys or censuses. Therefore, this chapter complements information already existing on data collection through censuses or surveys, and does not serve as a substitute for it.


      5For example, the 2014 United Nations publication Guidelines for Producing Statistics on Violence against Women: Statistical Surveys and the 2005 United Nations publication Guide to Producing Statistics on Time Use: Measuring Paid and Unpaid Work.

  • + References
    • Grosh, Margaret, and Paul Glewwe, eds. (2000). Designing Household Survey Questionnaires for Developing Countries: Lessons from 15 years of the Living Standards Measurement Study. Washington, D.C.: World Bank.

      Hedman, Birgitta, Francesca Perucci and Pehr Sundström (1996). Engendering Statistics: A Tool for Change. Stockholm: Statistics Sweden.

      United Nations (2005). Household Sample Survey in Developing and Transition Countries. Studies in Methods, Series F, No. 96. Sales No. E.05.XVII.6.

      _                          (2008). Principles and Recommendations for Population and Housing Censuses. Revision 2. Statistical papers, Series M, No.67/Rev.2. Sales No. E.07.XVII.8.

      _                       ,, Economic Commission for Europe, and World Bank Institute (2010). Developing gender statistics: a practical tool. Geneva. ECE/CES/8.

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