Mainstreaming a gender perspective into statistics means that gender issues and gender-based biases are taken into account systematically, in the production of all official statistics and at all stages of data production (Hedman et al, 1996; United Nations Statistics Division, 2001a; 2001b; United Nations, 2002; 2006). The Inter-Agency Expert Group on Gender Statistics and the Global Forums on Gender Statistics organized by the United Nations recognized that it is important to institutionalize gender statistics in all sectors to secure its sustainability (United Nations, 2006; 2009; 2012). Gender statistics produced as an “add-on” field are often marginalized; fail to reach a wide range of users, including policy makers in domains other than gender-equality, analysts, and researchers; and their production may be more dependent on irregular economic and human resources. Mainstreaming a gender perspective into the national statistical system may also lead to a more efficient coverage of gender issues and better coordination among data collection programmes in producing gender statistics.
National statistical systems need to regularly collect, analyse and disseminate data that address relevant gender issues. Gender statistics should document women’s and men’s participation in and contributions to all social and economic areas; and reflect underlying causes and consequences of gender inequality (Hedman et al, 1996; United Nations, 2002). The coverage of gender issues in the official statistics and their adequacy should be regularly reviewed, as requested by the Beijing Platform for Action (para 207 (b)). The review should make clear whether relevant gender issues, as defined by major data users, are covered by exiting data collection programmes and are made available to the users. Based on the review, the strategy of gender mainstreaming can involve collecting new types of data; expanding data collection in some areas to fill existing knowledge gaps; or better dissemination of data already collected (Hedman et al, 1996; United Nations, 2002). The strategy of gender mainstreaming should be based on strong collaboration between users and producers of data; strong internal coordination within the national statistical office and within the national statistical system; and data-sharing agreements between the national statistical offices and other agencies of the national statistical system or other producers of data.
Gender-sensitive concepts and methods should be used in data collection in all statistical fields. In order to provide reliable comparisons between women and men, gender statistics need to correctly measure women’s and men’s participation and contribution in society (Hedman et al, 1996). Conventional concepts and methods used in data collection are often inadequate to reflect the realities of women and men. For example, some women’s activities and contribution to economy and society are not adequately captured in statistics if old concepts of work and labour force, that do not take into account work, are used (see for example section on “Work” in chapter 2).
The units of enumeration and units of data collection should be adequately chosen to support the production of data that would show meaningful gender differences. For example, gender statistics in agriculture should be based on an adequate coverage of all agricultural holdings, including small holdings where women are predominant; include information on farm labour disaggregated by sex, age and other social and economic characteristics; and cover aspects of management and ownership of agricultural resources at the most disaggregated level possible, such as sub-holding and individual level.
Furthermore, new concepts and new methods of data collection should be used for the production of gender statistics. For example, recent methodological developments in time use surveys, violence against women surveys, or changes toward more comprehensive statistics in national accounts so that unpaid work is covered, should be integrated in the production of national statistics.
Improvement of content, methods, classifications, and measurements from a gender perspective should be made part of the ongoing work to improve all statistical sources – censuses, surveys and administrative systems (Hedman et al, 1996). Mainstreaming a gender perspective into data collection programmes involves: review and revision of the conceptual basis of data collection tools; review and revision of coding and classification systems and terminologies; gender training for all personnel involved in data collection; media campaigns that include gender specific messages; gender-sensitive selection of field interviewers; and reviewing and revising tabulations and data presentation and dissemination (Corner, 2003).
Presentation and dissemination of gender statistics should reach all potential target groups. Most often, existing data are not fully exploited for obtaining gender statistics (United Nations, 2009). Furthermore, data are often analysed and presented without considering users’ needs and thus fail to reach the target audiences (Hedman et al, 1996). However, presentation and dissemination of data are a crucial area of work in gender statistics. Gender statistics and results of data-based gender analysis should be disseminated to a wide range of users with a clear language that highlights gender-based causes and consequences and their policy implications (United Nations, 2002).
Dissemination of gender statistics should not be limited to gender-focused reports and databases. Restricting the activities concerning gender statistics to the compilation and dissemination of sex-disaggregated data and gender-sensitive indicators in gender publications only limits the audience and users of data. This restrictive approach may also perpetuate the perception that gender statistics are useful for women or gender’ advocates only. Gender statistics need to be taken into account not only in policies and programmes created to reduce gender inequality, but in all policies and programmes. It is important that statistics made available on a regular basis to policy makers include a gender dimension. As recommended by the Beijing Platform for Action, governments should use more gender-sensitive data in the formulation of policy and implementation of programmes and projects (United Nations, 1995; para 207 (a)). Presentation of gender statistics in regular statistical products produced by national statistical system increase the accessibility of gender statistics and their chances of being taken into account in policy making. If these documents fail to highlight the importance of the goal of gender equality and to incorporate relevant gender perspectives, an important opportunity is lost (United Nations, 2002).
Mainstreaming a gender perspective in data collection and presentation should be seen as part of the overall process of improving the quality of data produced by national statistical systems. Four components of the overall statistical data quality are particularly impacted (UNECE and World Bank Institute, 2010):
Relevance – defined as the degree to which statistics meet the needs of users. Gender mainstreaming in statistics entails taking into account users’ needs. Gender statistics aim to address gender issues that are defined as relevant by policy makers, advocates, researchers and the public.
Accuracy – defined as the closeness of statistical estimates to true values. Gender mainstreaming in data collection has a crucial role in reducing bias in data collection. For example, use of gender-sensitive data collection tools can prevent underreporting of women’s economic activity, underreporting of violence against women, or undercounting of girls, their births or their deaths.
Accessibility of data. Data on a variety of topics that are often associated with women’s interests are becoming available, such as time use statistics, violence against women, or statistics on family-work balance. Many gender statistics programmes also aim at making relevant gender-sensitive statistical information accessible to a wide range of audiences.
Clarity - related to presentation of data as well as to the availability of information on data quality and appropriate metadata. Gender mainstreaming pays particular attention to the dissemination of statistics in formats that are easily understood by a wide audience; and making clear the limitations of data collected based on concepts and methods that are not gender-sensitive.