Pierre Bourdieu wrote in 1977 that ‘what is essential goes without saying because it comes without saying: the tradition is silent, not least about itself as a tradition’.91 Whiteness and maleness are silent precisely because they do not need to be vocalised. Whiteness and maleness are implicit. They are unquestioned. They are the default. And this reality is inescapable for anyone whose identity does not go without saying, for anyone whose needs and perspective are routinely forgotten. For anyone who is used to jarring up against a world that has not been designed around them and their needs.
The way whiteness and maleness go without saying brings me back to my bad date (OK, dates), because it is intrinsically linked to the misguided belief in the objectivity, the rationality, the, as Catherine Mackinnon has it, ‘point-of-viewlessness’ of the white, male perspective. Because this perspective is not articulated as white and male (because it doesn’t need to be), because it is the norm, it is presumed not to be subjective. It is presumed to be objective. Universal, even.
This presumption is unsound. The truth is that white and male is just as much an identity as black and female. One study which looked specifically at white Americans’ attitudes and candidate preferences found that Trump’s success reflected the rise of ‘white identity politics’, which the researchers defined as ‘an attempt to protect the collective interests of white voters via the ballot box’.92 White identity, they concluded, ‘strongly predicts a preference for Trump’. And so did male identity. Analysis of how gender affected support for Trump revealed that ‘the more hostile voters were toward women, the more likely they were to support Trump’.93 In fact, hostile sexism was nearly as good at predicting support for Trump as party identification. And the only reason this is a surprise to us is because we are so used to the myth of male universality.
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 a subjective point of view. In such a framing, women are set up to be forgettable. Ignorable. Dispensable – from culture, from history, from data. And so, women become invisible.
Invisible Women is the story of what happens when we forget to account for half of humanity. It is an exposè of how the gender data gap harms women when life proceeds, more or less as normal. In urban planning, politics, the workplace. It is also about what happens to women living in a world built on male data when things go wrong. When they get sick. When they lose their home in a flood. When they have to flee that home because of war.
But there is hope in this story too, because it’s when women are able to step out from the shadows with their voices and their bodies that things start to shift. The gaps close. And so, at heart, Invisible Women is also a call for change. For too long we have positioned women as a deviation from standard humanity and this is why they have been allowed to become invisible. It’s time for a change in perspective. It’s time for women to be seen.
PART I
Daily Life
CHAPTER 1
Can Snow-Clearing be Sexist?
It all started with a joke. It was 2011 and officials in the town of Karlskoga, in Sweden, were being hit with a gender-equality initiative that meant they had to re-evaluate all their policies through a gendered lens. As one after another of their policies were subjected to this harsh glare, one unfortunate official laughed that at least snow-clearing was something the ‘gender people’ would keep their noses out of. Unfortunately for him, his comment got the gender people thinking: is snow-clearing sexist?
At the time, in line with most administrations, snow-clearing in Karlskoga began with the major traffic arteries, and ended with pedestrian walkways and bicycle paths. But this was affecting men and women differently because men and women travel differently.
We lack consistent, sex-disaggregated data from every country, but the data we do have makes it clear that women are invariably more likely than men to walk and take public transport.1 In France, two-thirds of public transport passengers are women; in Philadelphia and Chicago in the US, the figure is 64%2 and 62%3 respectively. Meanwhile, men around the world are more likely to drive4 and if a household owns a car, it is the men who dominate access to it5 – even in the feminist utopia that is Sweden.6
And the differences don’t stop at the mode of transport: it’s also about why men and women are travelling. Men are most likely to have a fairly simple travel pattern: a twice-daily commute in and out of town. But women’s travel patterns tend to be more complicated. Women do 75% of the world’s unpaid care work and this affects their travel needs. A typical female travel pattern involves, for example, dropping children off at school before going to work; taking an elderly relative to the doctor and doing the grocery shopping on the way home. This is called ‘trip-chaining’, a travel pattern of several small interconnected trips that has been observed in women around the world.
In London women are three times more likely than men to take a child to school7 and 25%8 more likely to trip-chain; this figure rises to 39% if there is a child older than nine in the household. The disparity in male/female trip-chaining is found across Europe, where women in dual-worker families are twice as likely as men to pick up and drop off children at school during their commute. It is most pronounced in households with young children: a working woman with a child under the age of five will increase her trip-chaining by 54%; a working man in the same position will only increase his by 19%.9
What all these differences meant back in Karlskoga was that the apparently gender-neutral snow-clearing schedule was in fact not gender neutral at all, so the town councillors switched the order of snow-clearing to prioritise pedestrians and public-transport users. After all, they reasoned, it wouldn’t cost any more money, and driving a car through three inches of snow is easier than pushing a buggy (or a wheelchair, or a bike) through three inches of snow.
What they didn’t realise was that it would actually end up saving them money. Since 1985, northern Sweden has been collecting data on hospital admissions for injuries. Their databases are dominated by pedestrians, who are injured three times more often than motorists in slippery or icy conditions10 and account for half the hospital time of all traffic-related injuries.11 And the majority of these pedestrians are women. A study of pedestrian injuries in the Swedish city area of Ume? found that 79% occurred during the winter months, and that women made up 69% of those who had been injured in single-person incidents (that is, those which didn’t involve anyone else). 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.
A five-year study in Sk?ne County uncovered the same trends – and found that the injuries cost money in healthcare and lost productivity.12 The estimated cost of all these pedestrian falls during just a single winter season was 36 million Kronor (around ￡3.2 million). (This is likely to be a conservative estimate: many injured pedestrians will visit hospitals that are not contributing to the national traffic accident register; some will visit doctors; and some will simply stay at home. As a result, both the healthcare and productivity costs are likely to be higher.)