Using data to enable women's empowerment

Using data to enable women's empowerment

Using data to enable women's empowerment

Lack of sufficient information on gender-wise data on land and other economic assets is a huge deterrent to the feminist movement in the country, notes Amrita Nandy. 

Severe arthritis has left Shanti, 68, nearly disabled. Bent with age, she limps through her days in acute pain, barely being able to cook or clean for herself. Single by choice, this retired nurse, who is based in Delhi, is without any physical support ever since her brother moved abroad to greener pastures.

Shanti’s case isn’t unique; in fact, there would be thousands of women across India facing similar ordeals. Yet, despite the pervasiveness of their situations, issues such as lack of assistance for the disabled and elderly or abuse of domestic workers do not receive enough public attention. What is of even greater concern is the fact that these varying contexts of women’s lives feature neither in macro-level research data, nor in the policymakers’ folios.

And if and when they do figure, are the analyses of gendered realities complex and meticulous enough to reflect all the multiple variables? These are some of the concerns and questions raised by Approaching Data Sources: A Gender Lens, a one-of-its-kind report prepared by the Centre for Women’s Development Studies (CWDS), New Delhi, with support from the United Nations Population Fund (UNFPA).

Focus on gender
According to Frederika Meijer, country representative, UNFPA India, “At present, we have at best, a partial snapshot of the status of women and girls in India because gender data is limited. This absence of good quality data spans different domains, be it health, education and social status or political participation and economic empowerment. This study is an attempt to assess the different data sources and their contribution to developing the perspective on Indian women’s lives. It also provides recommendations on how the existing data sources can be further improved, and what additional critical data needs to be collated to build a comprehensive understanding.”

While there is a wide quantum of data available, the data sources do not always provide an extensive picture. Although gender-focused information is available and gains have been made in statistics on gender inequalities, gaps, errors, inconsistencies and deficiencies continue.

Significantly, the report reviews literature on gender indicators and macro data sources, such as the Census of India, National Sample Survey Office (NSSO), and the National Family Health Survey (NFHS), to examine their usefulness to source data on women and girls and to analyse women’s status in India. It does so by focusing on certain themes vis-à-vis women: health, educational and economic status, violence against women, and
demographic, social and political status.

Women’s ownership of land and assets is another area that is very significant, particularly because it is intertwined with many other dimensions of women’s lives, such as health and wellbeing, access to education, financial independence, and ability to make and influence decisions, especially those related to their lives. Even so, there is very little data in this context.

Professor Neetha N, the lead researcher from CWDS, agrees, “The absence of gender-wise data on land and other economic assets is a crucial limitation of the existing statistics in India. This can be addressed to a large extent if all the existing data collected on these variables at the household level can be sex-disaggregated. The NSSO can also undertake a separate survey on women’s ownership of assets, including land.”

Besides dearth of actual data, researchers and experts are also worried about insufficient or substandard data. Professor Vimala Ramachandran of the National University of Educational Planning and Administration (NEUPA) highlights the challenge posed by the lack of detailed evidence on the educational scenario in the country. She says, “There is no dropout data in DISE (District Information System for Education) but SES (School Education Statistics) does offer dropout rates for state and district levels.

However, when we try to juxtapose the high enrolment data with the dropout numbers, one is left wondering how the Gross Enrolment Ratios continue to be high in higher classes when so many children are discontinuing their education after the primary level.

Though both the NSSO and NFHS gather data on reasons for drop-out, some of the categories used are inadequate in capturing the gender differences at play. For example, the percentage of those who offer the broad reason of “not interested in studies or going to school” is really high. But this explains nothing: is it because they do not learn anything in school or because there are factors like discrimination against girls at play?

Of course, the aforementioned flaws cannot be addressed only by creating new guidelines for data collection or devising better methodologies. What is required is a paradigm shift in the way data collection is viewed and the way data is used. Dr Indira Hirway, director, Centre for Development Alternatives in Ahmedabad, puts it plainly, “The present male-oriented statistical paradigm takes not only a partial, but a highly distorted view of our economy and society. We need to expand and reorient it to give full visibility to women’s concerns.”

Apart from collecting additional data to fill in the gaps, she calls for developing fresh tools for analysing the available data as well as the use of new statistical survey techniques – like time-use surveys – to highlight gender related issues in our statistical systems. Indeed, it’s only when such measures are put into practice that strategies for women’s empowerment will be evidence-based, drawn from the lived realities of women.

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