“The presumption that what is male is universal is a direct consequence of the gender data gap. Whiteness and maleness can only go without saying because most other identities never get said at all. But male universality is also a cause of the gender data gap: because women aren’t seen and aren’t remembered, because male data makes up the majority of what we know, what is male comes to be seen as universal. It leads to the positioning of women, half the global population, as a minority. With a niche identity and subjective point of view. In such a framing, women are set up to be forgettable. Ignorable. Dispensable – from culture, from history, and from data. And so, women become invisible.”
It is difficult to read this book without succumbing to a sense of both rage and frustration. Rage at the endemic discrimination against women which seems hard baked into all areas of society, all deriving from the often-unacknowledged assumption that women are the
deviation from the male norm. And frustration at the speed of change in a society which has known about many of these issues for a long time but seems to have made little progress in addressing them.
“The result of this deeply male-dominated culture is that the male experience, the male perspective, has come to be seen as universal, while the female experience–that of half the global population, after all–is seen as, well, niche.”
The depth and range of research that went into this book is breath-taking. The author’s examples touch on almost every area of life, and consistently return to the same conclusion: women just haven’t been thought about when it comes to the design of the constructed world we live in. It is hard to pick representative examples from the book, but here goes: at Google, which likes to think of itself as a progressive company, they hadn’t realised that parking spaces for pregnant women shouldn’t be at the back of the car park until the Chief Operating Officer fell pregnant; when first launched the Apple Health app didn’t include a menstrual cycle tracker; car crash dummies are 1.7m tall, the size of the average man, leading directly to women being 47% more likely to be seriously injured if they are in a collision; the average smartphone is 5.5 inches long and is too big for most women’s hands; speech-recognition software is trained on recordings of male voices and therefore much more likely to understand men. I could go on – this is not a book short on evidence or examples.
But it doesn’t have to be like that. This is not just a collection of evidence, powerful though that would be on its own. It is a manifesto, a rallying call for change. It is not enough to just witness this inequality; we should not accept women being treated as an anomalous version of masculinity and data collection should recognise sex and always consider how men and women are impacted differently.
“Closing the gender data gap is only step one. The next, and crucial step, is for governments and organisations to actually use that data to shape policy around it. This isn’t happening.
(page 120)
I am well aware that it is going to seem churlish of me to write about one of the very few passages in this book that I disagree with, but I think the issue is sufficiently important to address. In Chapter 12 ‘A Costless Resource to Exploit‘, the author writes about the post-2010 General Election austerity policies of public sector cuts. She describes how these cuts fell on women particularly hard (although you could add people with disabilities, ethnic minorities, Scots, Welsh, Irish, Northerners and the working class to that list) and observes that by comparison “men in the richest 50% of households actually gained from tax and benefit changes since July 2015”. So, an ideologically hard-Right Government cuts benefits, attacks the poor and gives tax breaks to the middle classes – Criado Perez rightly asks “So why is the UK Government enacting policy that is so manifestly unjust?” Her answer I have to say made me splutter:
“The answer is simple: they aren’t looking at the data”!!
Really? So it is not that there is a gender-gap in the data, which has been the central thesis of the book thus far, but that the Government and the thousands of civil servants that advise it have either chosen or forgotten to look at the data forecasting the impact of their cuts before implementing them. I can imagine George Osborne sitting in his office at the Evening Standard reading this chapter and saying “If only someone had told me that closing all those children’s centres, shutting down Sure Start, cutting funding to local Government, imposing the bedroom tax etc would have been damaging to working people and women in particular. If I had known that of course I wouldn’t have cut public spending and given tax breaks to the rich.”
This is important, because if we accept Criado-Perez’s idea that the problem is the data gap (which unquestionably exists in many areas) then the obvious remedy is to gather more data. That would no doubt help, but I struggle to believe that it would address the injustices in society on its own. Because there are plenty of situations where we have more than enough data, we just have politicians and people in power who choose not to use that data. Equal pay is an obvious example – we have a vast amount of data about how much people are paid, not least through the income tax system, yet the pay gap between men and women remains shamefully high. Do we need more data as to why that is, or do we just need to do something about it, and if so what? (Incidentally the Office for National Statistics has got a wonderfully detailed report on the gender pay gap on its website.)
Perhaps I am being unfair. Elsewhere the author is much more direct about the issue of whether the problem is missing data, or the willingness to use the data to confront inequality. It’s clearly both, and the motivations ascribed to the Government when imposing austerity were hyperbole.
The only other critical observation I would make is that Criado-Perez is inconsistent in her treatment of unpaid work. In Chapter 12 she points out that it is a political choice to exclude unpaid work, done largely by women, from measurements of national wealth and economic activity, usually expressed as GDP (gross domestic product). She illustrates how much GDP would increase in various countries if unpaid work was included in the measurement. But later she argues that
“Increasing the amount of unpaid work women have to do (by closing children’s centres, for example) lowers their participation rate in the paid labour force. And women’s paid labour-force participation rate has a significant impact on GDP.”
Invisible Women, pages 245-6
Enabling women to undertake paid work by providing adequate childcare would only raise GDP if we exclude the economic value of unpaid work from that measurement? Otherwise women would just be swapping unpaid work in the home for paid work outside of it. The actual value generated would be neutral.
These points might seem like nit-picking, but there is a far more serious issue that goes unaddressed here. The author treats data as if it is neutral, objective, the elusive source of answers to any question if it is collected correctly or if just enough data is gathered. But it’s not. It is possible to frame or interpret data in many ways. It isn’t passive – the exact same data set can be read to mean entirely different things (we’ve all seen those drawings – is it a duck or a rabbit?). Data can be twisted to make difference seem less drastic, false correlations can be drawn, how data is collected and presented can make huge differences to what it appears to tell us, and of course numbers can be manipulated depending on the question asked. Ben Goldacre’s Bad Science has some fascinating evidence on this, showing how it is possible to manipulate the results of supposedly double-blind trials simply by how you select your participants. We have seen during the recent Covid 19 epidemic that it is possible to the collect and present data to show how successful the UK Government’s handling has been despite it being seen by the rest of the world as an unmitigated disaster. Data is political.
Criado-Perez doesn’t directly address transgenderism, but it is an underlying topic in many sections of the book. A book called Invisible Women needs a working definition of ‘women’ for starters. One of the structural responses to the public discussion of transgender issues has been the introduction of gender-neutral toilets in public spaces. Criado-Perez is not sure that this is the correct approach. Not only does it reduce the availability of toilets for women (because they need to use stalls) but:
“We have learned from so many mistakes in the past that women are at a greater risk for sexual assault and violence if they don’t have separate bathrooms” (quoting an Amnesty International official).
Page 303
And on the topic of transwomen competing in women’s sport, the author provides the following significant evidence (I have removed the half a dozen or so footnotes from this quote, which provide evidence for each of the statistics quoted, but they are there to be checked if required) :
“Upper-body mass is approximately 75% greater in men because women’s lean body mass tends to be less concentrated in their upper body, and, as a result, men’s upper body strength is on average between 40-60% higher than women’s (compared to lower-body strength which is on average only 25% higher in men). Women also have on average a 41% lower grip strength than men, and this is not a sex difference that changes with age: the typical seventy-year-old man has a stronger hand grip than the average twenty-five-year-old woman. It’s also not a sex difference that can be significantly trained away: a study which compared ‘highly trained female athletes’ to men who were ‘untrained or not specifically trained’ found that their grip strength ‘rarely’ surpassed the fiftieth percentile of male subjects. Overall, 90% of the women (this time including untrained women) in the study had a weaker grip than 95% of their male counterparts.
Food for thought.
This is not a book to be rushed, but one once read to keep on the shelf for reference. It should be compulsory reading for anyone in a position of authority whether in Government or private enterprise. It’s a landmark study that will be looked back on in decades to come, hopefully as a record of how we got things wrong in the bad old days.
The Reading Bug 