Why we need better, more local data to promote gender equality

A panel discussion yesterday looked at how the 2021 census can be used to promote greater gender equality at a local level.

Illustration showing ratio numbers

 

A new gender index will draw on census data to give a local picture of gender inequality, a panel discussion heard yesterday.

The panel, hosted by the Global Institute for Women’s Leadership [GIWL] and chaired by MP Stella Creasy, addressed the issue of how we can use census data to address gender inequality.

Dr Caitlin Schmid, a research fellow at the GIWL, has been working on a gender equality index which will measure and map gender inequity at a local and regional level across most of the UK. Northern Ireland is not included because it collects limited gender-related data since it is not party to the Equality Act which makes data collection mandatory.

The index is in response to research showing that gender equality is experienced differently in different areas and that the UK has high levels of regional inequality. Dr Schmid said that many gender indices are global and that where local data exists it is not often accessible. 

Gender employment gaps, for instance, show a 3.5% gap in Scotland, compared to a 6.3% one in the North West and a 9.3% gap in London. More locally, data showed a lot of variation even in one region. In Greater Manchester, for instance, the gender employment gap is 2.3% in Trafford, 8.3% in Manchester and 15.3% in Rochdale – more than double the British average.

The index draws on the 2021 census and will provide a benchmarking tool for research as well as an accessible, user friendly website and will, for example, look at the gender difference between paid and unpaid work as well as issues like health and violence. It can be used, said Dr Schmid, for everything from informing policy to knowledge sharing between different local authorities about what works.

The need for gender disaggregated data

Also on the panel was campaigner Caroline Criado-Perez, author of the book Invisible Women. She spoke about the lack of good data on women, given most is based on a male model. She said almost everything, from phones and cars to work, is designed around men which is why it doesn’t often work well for women. She took cars as her example, saying car crash dummies used to test car safety are based on the average man. There is a female version, but it is just a scaled down version of the male one and it’s only used in passenger seats. Women, however, are not scaled down men, said Criado-Perez, and they do drive. Their bodies are different and so car crashes will have a different impact on them. For example, a seatbelt is designed to catch on men’s hips, but on women it will ride up, which could cause fatal injuries.

Criado-Perez said some progress had been made on this by some countries, but most were “massively taking their eye off the ball” when it comes to Artificial Intelligence, which, she said,  amplifies existing biases. “AI trained predominantly on male data will be worse,” she stated.  We need to ensure there is a gendered analysis of data and that safeguards are taken with the data used to fuel AI “to prevent us making the world worse”, said Criado-Perez. “Data is not just about abstract numbers,” she said. “It drives our world and the decisions that affect every one of us. It really matters when you leave out half the world. Always sex disaggregate your data.”

Good local data

Other speakers included Dr Liz Hind from the Women’s Budget Group who outlined how data could be used for women’s benefit. Showing charts which depict starkly the unpaid care gender gap by age showing a big bulge for women aged between 45 and 70, she said the Women’s Budget Group is keen to pull together useful data and work with others to explain it in order to promote policies that drive greater equality.

Dr Hind added that data had to be used at a local level to implement change, citing the Local Data Project and increasing interest from local authorities in setting up equality panels to debate the issues. She cited transport as one example. Research shows women use public transport differently than men. Criado-Perez said the way data is gathered on public transport use shows a male bias since unpaid work and leisure are lumped together, whereas travel for work is a separate category. If unpaid work, done mainly by women, and paid work were separated out, there would be just a 1% difference in usage which could affect transport planning decisions, she said.

Jennette Arnold, former chair of the London Assembly, spoke of the need for an intersectional approach to data that highlights the cumulative impact of different forms of discrimination and bias. She spoke of how she used the data produced by the TUC for Equal Pay Day to drive change at the level of the Greater London Authority. It now produces a GLA data index which is used by organisations including the Metropolitan police and Transport for London. 

Stella Creasy said good data which highlighted the important role childcare plays in our economic infrastructure was vital in the campaign for universal childcare. However, she said that, in its Budget, the Government had only addressed the demand side of the equation – stoking more demand for childcare through subsidies – without dealing with the supply side, with funding per place expected to fall short of the actual costs for nurseries. She predicted more nursery closures and a backlash if take-up of places did not increase. She said people would argue that “women wanted to stay at home all along”.



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