| dc.description.abstract | The relationship between gender and statistics is complex and often confusing. Early work was
confined to the presentation of statistics about women to inform research and programme
development to increase their status and monitor improvements in their lives.
However, identifying gender issues and changes in the status of women requires a comparison with the
situation of men. Publications on “Women in Statistics” were replaced by publications on “Women and
Men in Statistics” and disaggregation of statistics by sex became the main method for identifying
differences between women and men and for the production of gender statistics. In theory at least, it
became a requirement for the collection, compilation, dissemination and analysis of all individual-level
data.
While disaggregation by sex remains a basic tool for gender statistics, it can only identify differences
between women and men and gender issues that are addressed, directly or indirectly, in data collection.
As more gender issues reached the policy agenda, recognition of the lack of data on issues such as
violence against women, time use, unpaid work and family care demonstrated that gender statistics
must do more than just disaggregate existing data by sex. As a result, new surveys such as those on
violence against women were developed and others such as time use surveys were reinvented to fill
some of these data gaps, expanding our understanding of gender statistics in the process.
Gender differences and gender relations within survey populations and the statistical system as a whole
also potentially affect the quality of data, including data not directly concerned with gender issues.
Integrating a gender perspective throughout the statistical system to take account of these effects,
described as “engendering statistics,” is gradually being recognised as essential for the production of
quality data. However, it is a highly complex process involving the entire system and success is very
dependent on institutional arrangements.
The collection of good practices presents a number of country studies of good practices, each focusing
on a particular aspect of gender statistics. Paper writers were specifically requested to consider the role
of institutional factors and arrangements in the success of the good practice. Institutional mechanisms
for communications, collaboration and coordination proved to be especially important to ensure that
the gender statistics were useable, accessible, and actually used.
We hope that the analysis and innovative examples presented here will inspire and motivate colleagues
in other statistical offices to learn from these experiences and emulate their success. | en_US |
