Session Report
Liya Jomon
On the 4th day of the educational session initiated by IMPRI, Professor Vibhuti Patel, a visiting professor at IMPRI, was the speaker and she enlightened us with her knowledge on the topic of gender mainstreaming of data, monitoring, and evaluation. She started the session by thanking everyone.
The first topic she touched upon was gender mainstreaming.
She mentioned various gender equality indicators like education, power, employment, violence, social security, and health, then she briefed about gender statistics: which were labeled as statistics that adequately reflect differences and inequalities in the situation of people of different genders in all areas of life.
Prof. Vibhuti mentioned how The Beijing Platform for Action, 1995 recommended that national, regional, and international statistical services should ensure that statistics related to individuals are collected, compiled, analysed, and presented by sex and age and reflect problems, issues, and questions related to all genders in society which would include all aspects of women’s and men’s lives, including their specific needs, opportunities, and contributions to society, differences in health, education, work, family life or general well-being.
It was also brought to the attendees’ notice how gender statistics should adequately reflect differences and inequalities in the situation of women, men, and transgender.
Concepts and definitions used in data collection must be responsive to the diversity of various groups of women, men, transgender persons, persons with disabilities, and their specific activities and challenges.
During this course, she highlighted the work of Maria Mies, a German professor of sociology, a Marxist feminist, an activist for women’s rights, and an author. It emphasized how the work done by women is often gone unnoticed, and how women are segregated in various aspects of everyday life.
The fact that women are exploited was made clear using the example of how women put in days of hard work and labor and get a minimal amount of money as a wage when the product that is produced by them is sold to different markets at double or triple their wages. To be precise, there are different forms of support provided by women which was divided into two part namely direct and indirect support. Such global supply chain support provided by women, like family labor, unpaid work, housework, driving water, fodder, etc, is not reflected in the final data system.
Gender Statistics are more than data segregated by sex
In this part, Professor Vibhuti highlighted how data collected has to reflect gender issues, along with other pointers. She gave various examples of injustice faced by women in different circumstances like the tsunami situation, where the newly rebuilt houses were in the name of men, and all single women were left homeless.
Situational analysis:
The dissemination of gender statistics to a large audience is crucial in reducing both gender stereotypes and the misrepresentation of the gender roles of women, men, gender minorities, persons with disabilities, and their contribution to society. To complement this argument, Prof. Vibhuti emphasized how a person in a wheelchair, or a woman who is not involved in a defined occupation is considered jobless, however, the fact could certainly be different.
Why gender statistics?
Prof. Vibhuti mentioned how women are at the bottom of the pyramid even though 2/3rd work of the world is done by women, however, they get only 10% of the overall income and own 1% of the wealth. Gender statistics are crucial in advancing data-based gender analysis and research.
Gender statistics provide researchers and analysts with quantitative data. Gender statistics are used in monitoring progress towards gender and the full and equal enjoyment of all human rights and fundamental rights by all genders. Gender equality means equal opportunities, rights, and responsibilities for all genders.
Construction of gender indicators
According to Prof. Vibhuti, gender statistics are the basis for constructing gender indicators and a useful tool for progress toward gender equality goals. Not all statistics are indicators. A statistic becomes an indicator when it has a reference point against which value judgements can be made. Indicators have a normative nature, in the sense that a change from the reference point (a norm or a benchmark) in a particular direction can be interpreted as “good” or “bad”.
Efficiency gain
Gender statistics have been the basis for proving that perspectives and gender equality can result in efficiency gains. Research has revealed that reducing gender inequality could significantly increase productivity, total national output, and the human capital of the next generation.
Poverty reduction strategy
The use of gender statistics can provide a more comprehensive understanding of the gender dimensions of poverty, which in turn can significantly change priorities in policy and program interventions. The use of gender statistics can provide a more comprehensive understanding of the gender dimensions of poverty, which in turn can significantly change priorities in policy and program interventions.
Gender-based violence:
Gender statistics have an important role in developing monitoring policies for the reduction of violence against women. Violence against women is an obstacle to the achievement of the objectives of equality, development, and peace.
Mainstreaming a gender perspective in statistics
Mainstreaming a gender perspective in statistics means that gender issues and gender-based biases are systematically taken into account in the production of all official statistics and at all stages of data production.
The Inter-department and Expert Group on Gender Statistics and the various ministries of the union government, departments of state government, and local self-government bodies must accept that it is important to institutionalize gender statistics in all sectors in order to secure its sustainability.
Preconditions for visibility of gender in statistics
- Relevance: 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 policymakers, advocates, researchers, and the public.
- Accuracy: 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, the use of gender-sensitive data collection tools can prevent underreporting of women’s economic activity, underreporting of violence against women and undercounting of girls, their births, and their deaths.
- Accessibility of Data: Data on a variety of topics that are often associated with women’s interests are becoming available, such as statistics on time use, violence against women, and family-work balance. Many gender statistics programs also aim to make relevant gender-sensitive statistical information accessible to a wide range of audiences.
- Clarity. This is related to the presentation of data as well as to the availability of information on data quality and appropriate metadata. Gender mainstreaming pays particular attention to disseminating statistics in formats that are easily understood by a wide audience and making clear the limitations of data collected on the basis of concepts and methods that are not gender-sensitive.
The session ended with a reality check to highlight the parity and gender bias faced by women, by showing some real data like the global gender gap index ranking and the percentage of women on companies’ boards of directors.
Acknowledgement: Liya Jomon is a research intern at IMPRI.
Read more session reports on web policy learning events conducted by IMPRI:
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