Bridging the gender data gap – Oxfam is looking for a researcher. Interested?

Oxfam’s research team is looking for a gender justice researcher. Closing date is Monday (30th May), so despite Deborah Hardoonhaving only one typing hand (bike accident, not nice), Deborah Hardoon explains why you should apply

In 1990 Amartya Sen wrote an editorial for the NY Times review of books that highlighted a numerical discrepancy with profound implications. He looked at data on birth rates – all over the world there are around 105 or 106 male children for every 100 female children. This is just the biology of reproduction. After birth, given the same amount of care and nutrition, girls do better than boys – we are hardier, better at resisting disease and live longer. As a result in Europe, Japan and the US, there are about 105 women for every 100 men. However in parts of Asia and North Africa, women do not fair so well. In China there were just 94 women for every 100 men and in the Indian state of Punjab, just 86 women. Sen calculated that the difference between the gender ratios in countries where men and women generally receive equal treatment  and the ratio in parts of South Asia, West Asia, and North Africa. More than 100 million women are “missing.” The cause was a combination of selective abortion and neglect.

‘These numbers tell us, quietly, a terrible story of inequality and neglect leading to the excess mortality of women’ he concluded.

Sen’s path-breaking work exemplifies the value of gathering and analysing data that is both disaggregated by gender and that measures what really matters. We have plenty of evidence of discrimination and the abuse of women’s rights. From graphic examples of gender based violence and rape to economic and political exclusion and everyday sexism experienced by women and girls. This sort of evidence and the associated stories of the people affected paint a picture of a world in which women continue to face injustice on many levels. Beyond brining these injustices to life, we also know that quantifying issues is incredibly useful – for spotting trends and associated causes/effects, but also for communicating the scale and depth of issues using stark statistics. By revealing and naming, scrutiny and action become possible.

women like men only cheaperWe live in a world today where data, Big and small, can tell us everything from how much a government spends on each department to the next book we are going to read. So it is incredibly frustrating that despite the fact that we recognise that there is a gender pay gap and very few women make it to the top, at the national level we still don’t really know what the income differences are between men and women, nor how much decision-making power men and women have over how their household income is spent nor if trends are getting better/worse. This is because income and asset ownership is generally measured at the household (not individual) level. Bad data and tenuous extrapolations can be unhelpful and undermining, some gender related stats have been particularly contentious.

Which is why there is a huge need for better data, as recognised by the Bill and Melinda Gates Foundation’s new commitment to spend $80 million to plug the gender data gap. But data alone isn’t enough. We also need great researchers and analysts to dig into the data we have, inform the development of new indicators and methodologies to measure what matters and communicate that widely, particularly making the data come alive, demonstrating what it really means for women and girls.

That is why we are currently recruiting for such a person. We are looking for a skilled researcher who is great with numbers and looking to apply this to issues of gender justice. This will involve exploring how to measure and analyse empowerment and exploring women’s rights issues, particularly from a quantitative perspective, in both our programme work on the ground and campaigns on Rights in Crisis, Inequality and Climate Justice. If this sounds like you, please apply by May 30th.

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2 Responses to “Bridging the gender data gap – Oxfam is looking for a researcher. Interested?”
  1. Alice Evans

    I agree, we lack data about many dimensions of gender inequalities, such as asset ownership. I also agree that more data analysis will enhance our understanding of ‘how change happens’. And it’s great to see more funding for gender.

    But I wonder if you could please recommend some readings showing how more data strengthened feminist movements or otherwise led governments to prioritise gender equality?

    As far as I’m aware, son preference is significantly declining South Korea. This has been largely driven by urbanisation: seeing women demonstrating their equal competence in socially valued domains has eroded the gender beliefs and historical preference for sons. In China, son preference is lower in villages with a high share of female outmigration to city jobs. I’m not sure what role data has played in these structural shifts?

    Further, there are many areas where we do have a lot of data, but struggle to get evidence-based policy: gender-based violence, women’s share of care work, men’s predominance of prestigious positions, men’s high rates of suicides.

    I *think* we also have data for some of the issues you mention. Demographic and Health Surveys record men and women’s reported participation in expenditure of their respective incomes, as disaggregated between daily and large household purchases. Is your concern here about the inaccuracy of these panel data sets?

    And some of this data is used by governments: e.g. benchmarking indicators can motivate progress

    But I wonder if there’s an opportunity cost of spending more on gender data. Could it be better spent on projects like Raising Her Voice? As I recall, Oxfam’s reports found those projects worked well at £120,000 per year. Could the gender data money have been better spent elsewhere? – or at least on areas where there is evidence that expenditure enhances gender equality.

    These are just questions. I really don’t have a strong view on this and would be grateful for your guidance on readings showing how more data can help.