Invisible Women

Book Cover of Invisible Women by Caroline Criado PerezWhat with the snow hitting us right about now, it seems like a good time to talk about how snow removal can be sexist. Yup. Snow removal. Sexist.

Edited: Here are the links to Canadian stats! Thank you Victoria!

Northern Sweden has been collecting data on hospital admissions for injuries since 1985, and found in icy or slippery conditions, pedestrians were injured three times more often than motorists, “and account for half the hospital time of all traffic-related injuries”. Furthermore:

[T]he majority of these pedestrians are women. A study of pedestrian injuries in the Swedish city of Umeå found that 79% occurred during the winter months, and that women made up 69% of those who had been injured in single-person incidents… two-thirds of injured pedestrians had slipped and fallen on icy or snowy surfaces, and 48% had moderate to serious injuries, with fractures and dislocations being the most common. Women’s injuries also tended to be more severe. (Criado Perez, c.1: Can Snow-Clearing Be Sexist?, Invisible Women).

Alright, so women are more likely to be injured in icy or slippery conditions (enough to end up in a hospital for treatment), with more severe injuries than men. But why? As it turns out, men and women tend to use different modes of transport, along with very different travel patterns, which is true worldwide to varying degrees (based on the limited sex-disaggregated data we have on the topic): whereas men are more likely to drive and “dominate access to [a household’s car]” (ibid; by which I assume Criado Perez means in man-woman households), with simple travel patterns that consist of commuting to and from town, women tend to walk and take public transport and have more complicated travel patterns, namely trip-chaining: making several interconnected trips at once. This is part of a larger discussion about unpaid labour, which is discussed throughout Invisible Women, but women’s travel patterns tend to include a cornucopia of tasks, including: dropping children off before heading to work; taking aging parents to the doctor; grocery shopping on the way home.

Seeing the data and this information about gender differences in travel patterns, Sweden changed the order of snow plowing to target sidewalks before main roads (because really, it’s a lot easier for the car to drive over snow than for a person to walk (or push a stroller) through the same amount of snow on the sidewalk). Let’s break it down. Considering that pedestrian injuries due to icy and slippery conditions account for, as stated above, “half the hospital time of all traffic-related injuries”, that’s no paltry amount of staff time and effort being devoted to women’s injuries – and this doesn’t even take into account the time this army of injured women need to take off work (paid or unpaid labour) to heal (or even just to go to the hospital in the first place). The conservative estimated cost of these pedestrian injuries throughout one winter was 36 million Kronor (approximately £3.2 million), which “was about twice the cost of winter road maintenance. In Solna, near Stockholm, it was three times the cost, and some studies reveal it’s even higher” (ibid.). All this to say, even if you don’t care at all about gender equality or women getting injured disproportionately, or you think that well in that case more women should just drive to solve this issue**… taking women and their needs into account when policy-making makes sense. I know the conclusion of that sentence was pretty self-evident, and it should be a no-brainer, but clearly, if the decision was made in the first place to plow the roads before taking care of the sidewalks, it wasn’t. It isn’t. Taking women into account doesn’t come naturally, clearly. This is why Invisible Women is such a necessary read, especially now: so that taking women and their needs into consideration will become natural.

*I feel like this is kind of the perfect unintended example of why Invisible Women is so necessary right now.

**I hope no one actually thinks of this as a productive line of thought.

 

There was actually an article on the CBC early on in 2018 about this: Should Ottawa Adopt Sweden’s Gender-Balanced Snow-Clearing Policies?, and the crux of that interview comes down to the decision being really based on how politicians and city planners envision the city, or what their ideal of the city to be (which… makes sense. Formulate a goal before actually taking action so we can aim for that goal; pretty straightforward). There’s also this other CBC article on Sweden’s snow-clearing policies & Ottawa, and one of the quotes from it I think illustrates the gender gap in data collection quite well – the basis of Invisible Women: “Part of the problem in Canada, she said, is actually getting the robust data to see who is benefiting from federal services and programs” (CBC.ca, Jan 22, 2018). Without this data, we can’t even get to know what needs to be done, exactly, and how to fix the issue. Can Sweden’s policy for snow-clearing be copied & pasted into Ottawa, or Toronto, or wherever? Where do we differ? Are the unequal hospitalizations during wintry conditions the same as they are in Sweden, with more women being admitted to hospitals for more serious injuries if roads are cleared before sidewalks? What’s the difference in snowfall between Ottawa & Sweden? What about differences in how people commute and how city planners would like them to? The difference in road conditions, in driving? Maybe I’m just not looking in the right place – I wouldn’t be too surprised, considering this isn’t my area of expertise – but I think even just these considerations I’ve quickly listed above are a good illustration of how missing data, or data that excludes women for being too different (from the “standard” or the “norm”, which is male. Which… I won’t get started, but please imagine my outrage), too difficult to include (because… hormones. Of course. But there’s also the fact that women do so much unpaid labour that they just don’t have as much time to participate in studies), are absolutely necessary to collect in order to make policies that are actually good for the people rather than mostly just for men.

There are so many chapters (all of them) that are absolutely infuriating and more frustrating than I can relay, and each is enlivened by examples of the multifarious ways in which women are short shrifted all over the world, with consequences ranging from inconvenient (e.g. voice recognition software recognizing men’s voices more readily than women’s; too-large phones for women’s hands) to disastrous or deadly(e.g. heart attack symptoms differ between men and women; disaster-relief being a second wave of danger for women). My favourite – I mean, all of the chapters, but this one was hilarious in a sort of “who approved this???” way – was probably this one: in the face of an earthquake that hit Gujarat in 2001, the disaster-relief rebuilding project built… wait for it: houses without kitchens, because “women weren’t included or even consulted in the planning process” (Criado Perez, c. 15: Who Will Rebuild?). AND IT HAPPENED AGAIN FOUR YEARS LATER. In Sri Lanka, after the Boxing Day tsunami, kitchenless homes were raised. And one more: “[a] related issue arises in refugee camps when humanitarian agencies distribute food that must be cooked – but forget to provide cooking fuel”. Who approves these decisions?

In the afterword, Criado Perez concludes quite neatly what the issues are, and what she is hoping will come of this publication. She outlines three ways in which women are defined in their relationship to the world:

  1. The invisibility of the female body, or more specifically the lack of consideration of women’s bodies in a world made with men in mind, which “has led to a world that is less hospitable and more dangerous for women to navigate” (Criado Perez, Afterword).
  2. On the other hand, the visibility of the female body in male sexual violence against women: “how we don’t measure it, don’t design our world to account for it, and in so doing, allow it to limit women’s liberty. Female biology is not the reason women are raped. It is not the reason women are intimidated and violated as they navigate public spaces. This happens not because of sex, but because of gender” (ibid.; emphasis mine)
  3. Unpaid labour: it’s the work women do – that girls are brought up to do more than boys are – the work without which this world would cease to run as it does right now.

One thing that Criado Perez emphasizes in the afterword is the following:

Failing to collect data on women and their lives means that we continue to naturalise sex and gender discrimination – while at the same time somehow not seeing any of this discrimination. Or really, we don’t see it because we naturalise it – it is too obvious, too commonplace, too much just the way things are to bother commenting on. (ibid.)

And before concluding with what should be fairly obvious by now what one thing can be done to close this gender data gap, Criado Perez also notes something that kept cropping up in her research: the excuses as to why this data gap exists. Women are too “unharmonious, too menstrual and too harmonal… travel patterns are too messy, their work schedules too aberrant, their voices too high… women are abnormal, atypical, just plain wrong” (ibid.). But the simple fact of reality is that women exist, no matter how much they’re cut out of data collection, how we refuse to see them: “Yes, simple is easier. Simple is cheaper. But simple doesn’t reflect reality” (ibid.).

So what do we do? How can we begin to change the gender data gap? It’s actually a pretty simple solution: “we must increase female representation in all spheres of life” (ibid.; emphasis mine). And the good news is, apparently women who rise up into positions of power or authority don’t forget quite as easily that women exist. I’ll leave you with this, and urge you to put yourself on hold or check out a copy of Invisible Women. It’s available as a book, an e-book through VPL’s OverdriveHooplaDigital, along with Markham’s Overdrive (accessible using your VPL card), and as an e-audiobook via OverdriveHooplaDigital.

5 thoughts on “Invisible Women

  1. Very interesting read! I do wonder if the snow removal thing has anything to do with the potential severity of the injury should things go sour. I realize this is anecdotal, but I know two people (one personally and one semi-personally) who were in automotive accidents and died—one man and one woman. Both were young; one had a wife and six-month-old child at home and the other was an English teacher. I know two other people (yes, both woman!) who slipped and fell on the ice and were injured. For one, I believe it cost her time off of work, which really sucks, I agree. I have also (several times) had the frustration of pushing a stroller through the snow: not an enjoyable experience and I would have really liked if the pathways weren’t so bad. Even still, I just wonder if because the consequences of slipping on the road behind the wheel of a car, the greater potential for death (I presume/ mostly owing to the high speeds)/ risk of swerving off into a pedestrian, if it might be a good reason to keep the roads cleared first? Just something I wondered about. I thought you brought up some really fascinating points! For example, I didn’t know that women made up the majority of pedestrians (the environment: “thank you, women”). I found this really interesting.

    Thanks for this one—keep ‘em coming!

    1. I’m really sorry to hear that, and I think you bring up a very good point! The data collected in Sweden discussed in Invisible Women only talks about the severity of injury for single-person incidents, so I’m not sure whether the average toll of automobile accidents might be worse than that of pedestrian incidents. Which is also part of the issue, right, that 1) this is all based on data in Sweden, and people might drive differently there than they do in Canada (among other differences that might affect how well this data works for Canada), and 2) we need more sex disaggregated data!

      1. It’s such an interesting topic, though! It was something I hadn’t read about before and it really got me curious (always a good thing–unless you’re a cat). I worried that my reading of it may be overly heuristic (just because you know someone who got salmonella poisoning and as a result are super careful with raw eggs, it doesn’t necessarily mean it’s a likely outcome). It’s easy to incline toward what you know via experience, whether or not it’s optimal information. I did do some searching, though, and found that in Canada, you’re about as likely to die in a motor vehicle accident as you are to die from chronic liver disease (just under 2, 500 deaths in 2009, according to data released by Stats Canada in 2012) with Males accounting for 1, 717 of motor vehicle accident deaths and females 689. Although accidental deaths are on the rise in Canada, it was difficult to find any stats that particularly deal with pedestrians, but I’d be interested to compare. I was able to find data about who is most at risk of injury—turns out, it’s young people! Canadians aged 12 to 19 had TWICE the proportion of injuries compared to any other age group. While sports were a big reason, if you look at stats for seniors specifically, household chores AND WALKING are the biggest culprits, which would tie into the snow clearing. In general, a fall was the most likely cause of injury in Canada by a significant margin, accounting for 1, 714 serious injuries (873 males and 841 females) (2009-2010). There are appendixes listing types of injuries (sprains, broken or fractured bones etc.) and seasons most likely to be injured in (summer was the season in which Canadians were most likely to sustain a serious injury, with winter a close second—fall is the safest season!). I’ll post the links below:

    1. Thank you so much for the links, Victoria! I have to say it’s not entirely a surprise that younger folks are at a greater risk of injury, but the degree to which they are more at risk is eye-opening. As you said, I’d also be interested in the comparison between accidental vehicular fatalities (between vehicles), vehicular accidents including pedestrians, and pedestrian accidents. On the particular topic of snow plowing and accidents vehicular and pedestrian in Canada v.s. Sweden, the difference in the collected stats makes me wonder: if Canada on the whole has more fatal vehicular accidents, as compared to Sweden’s more frequently occurring, more serious pedestrian accidents (v.s. rate of and seriousness of vehicular accidents, as is implied in Invisible Women if not outright said – I don’t have a copy of the title anymore, so I can’t double-check this right now unfortunately!), which is more preferable (assuming we would want to choose one or the other instead of allowing it to happen naturally)? And is there anything we can do to change it one way or the other (e.g. driving habits, traffic and construction, snow-plowing)? Or should we instead perhaps simply accept these differences and go forward from here, because those deep-seated differences that create the statistical differences are likely incredibly difficult to change even if we wanted to?

      Your comment actually reminded me of something I was thinking about while reading Invisible Women as well, that although I’m pretty sure that the examples taken from around the world by Criado Perez was probably done to highlight the way in which the gender gap in data collection/analysis only affects those living within a certain geography so much as everyone, I did get the feeling that the book as a whole would have benefited greatly from an analysis of the ways in which certain examples did or did not translate to other countries, and for what reason if they didn’t. (And also perhaps why despite the fact that they don’t necessarily translate one to one, the example should still be relevant – or not.)

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