Invisible Women: Data Bias in a World Designed for Men

Valuing cars over pedestrians is not inevitable. In Vienna 60% of all journeys are made on foot, in no small part because the city takes gender planning seriously. Since the 1990s Vienna’s head of gender planning, Eva Kail, has been collecting data on pedestrian travel and has installed the following improvements: improved and signed crossing locations (plus forty additional crossings); retrofitted steps with ramps for prams and bikes; widened 1,000 metres of pavement; and increased pedestrian street lighting.27

The mayor of Barcelona, Ada Callou, has shown similar determination to give her city back to pedestrians, creating what are called superilles or ‘superblocks’ – squared-off sections of the city with low speed limits open only to local traffic, with roads where pedestrians have equal priority with cars. Another example of easy changes that can be implemented to accommodate female travel patterns comes via London, where in 2016 the ‘hopper fare’ was introduced to the bus network.28 Previously, every time a user boarded a bus they were charged for a new journey, but under the new system users can now make two trips in one hour for the price of one. This change is particularly helpful for women because they were disproportionately penalised by the old charging system. This is not only because of women being more likely to trip-chain, but also because women make up the majority (57%) of London’s bus users (partly because it’s cheaper, partly because the bus is perceived as more child-friendly), and are more likely to have to transfer (which under the old system counted as a new trip).

The reason women are more likely to have to transfer is because, like most cities around the world, London’s public transport system is radial.29 What this means is that a single ‘downtown’ area has been identified and the majority of routes lead there. There will be some circular routes, concentrated in the centre. The whole thing looks rather like a spider’s web, and it is incredibly useful for commuters, who just want to get in and out of the centre of town. It is, however, less useful for everything else. And this useful/not so useful binary falls rather neatly onto the male/female binary.

But while solutions like London’s hopper fare are an improvement, they are by no means standard practice worldwide. In the US, while some cities have abandoned charging for transfers (LA stopped doing this in 2014), others are sticking with it.30 Chicago for example, still charges for public transport connections.31 These charges seem particularly egregious in light of a 2016 study which revealed quite how much Chicago’s transport system is biased against typical female travel patterns.32 The study, which compared Uberpool (the car-sharing version of the popular taxi app) with public transport in Chicago, revealed that for trips downtown, the difference in time between Uberpool and public transport was negligible – around six minutes on average. But for trips between neighbourhoods, i.e. the type of travel women are likely to be making for informal work or care-giving responsibilities, Uberpool took twenty-eight minutes to make a trip that took forty-seven minutes on public transport.

Given women’s time poverty (women’s paid and unpaid work combines into a longer working day than men’s), Uberpool might seem attractive.33 Except it costs around three times more than public transport and women are also cash poor compared to men: around the world women have less access to household finances than men, while the global gender pay gap currently stands at 37.8% (it varies hugely from country to country, being 18.1% in the UK; 23% in Australia; and 59.6% in Angola).34

There is, of course, an issue of resources here, but the problem is, to a certain extent, one of attitude and priorities. Although McKinsey estimates that women’s unpaid care work contributes $10 trillion to annual global GDP,35 trips made for paid work are still valued more than trips made for unpaid care work.36 But when I ask Sánchez de Madariaga if, in a city like London or Madrid, there is an economic argument for providing transport that caters for women’s care responsibilities she replied immediately. ‘Absolutely. Women’s employment is a really important input to GDP. For every percentage increase in women’s employment there is a greater increase in GDP. But for women to work, the city has to support this work.’ And one of the key ways to do this is to design transport systems that enable women to do their unpaid work and still get to the office on time.

When it comes to fixed infrastructure like subways and trains, Sánchez de Madariaga explains, there is not much you can easily or cheaply do to address this historical bias. ‘You can improve their accessibility,’ she says and that’s about it. Buses, on the other hand, are flexible and their routes and stops can and should be ‘moved and adjusted for need’, says Sánchez de Madariaga. This is, in fact, what Ada Callou has done in Barcelona, by introducing a new orthogonal bus route (a grid rather than a spiderweb, which is more useful for trip-chaining). Sánchez de Madariaga also argues that public transport needs to develop ‘intermediate services, something between a car and a bus. In Mexico they have something called terceros, which are really small, like a mini mini minibus. And they have shared taxis. These have a lot of flexibility, and, I think, could and should be developed to support women’s mobility.’

While much of the historical gender data gap in travel planning has arisen simply because the idea that women might have different needs didn’t occur to the (mainly) male planners, there is another, less excusable, reason for it, and that is that women are seen as, well, just more difficult to measure. ‘Women have much more complicated travel patterns,’ explains Sánchez de Madariaga, who has designed a survey to measure women’s care travel. And on the whole, transport authorities aren’t interested in women’s ‘atypical’ travel habits. Anastasia Loukaitou-Sideris, a professor of urban planning at UCLA, tells me that ‘oftentimes there is the perception from the part of transit operators that everyone has universal needs. Men, women, everything is the same. And this is completely untrue.’ She laughs in exasperation. ‘Talking to women riders they bring up a whole slew of different needs that are not being taken care of.’

To make matters worse, transport authorities are compounding the existing gender data gap by failing to separate the data they do have by sex. The annual transport statistics report37 created by the UK government’s Department of Transport includes a single statistic (on the gender breakdown of driving-test pass rates – in 2015/16 44% of women passed versus 51% of men), and a link to a page on a government website that hosts a report on gender and walking. The report has nothing to say on the gender breakdown of bus or rail usage, for example, even though this information is vital for planning a transport system that properly serves all its users.

India’s public transport agencies also don’t separate their data by sex,38 while a recent EU report bemoaned the paucity of gender-sensitive transport data, explaining that ‘this kind of data is not collected on a regular basis in the majority of European countries.’39 As in the UK, the US’s Transport Statistics Annual Report only mentions women twice: once in relation to driving licences and once in relation to walking.40 Unlike the UK, however, these references are not even presented as usable statistics, just generalised statements.

A more hidden data gap comes courtesy of the way transport agencies around the world present their data. On the whole, all travel for paid work is grouped together into one single category, but care work is subdivided into smaller categories, some of which, like ‘shopping’, aren’t distinguished from leisure. This is failing to sex-disaggregate by proxy. When Sánchez de Madariaga collected care-related travel data in Madrid, she found that the number of trips made for caring purposes almost equalled those made for employment purposes. And when she further refined the data by sex-disaggregating it, she found that care was ‘the single and foremost purpose of travel for women, in much the same way as employment is the main purpose of men’s travel’. If all travel surveys were to do this, she argues, planners would be forced to take care travel as seriously as employment travel.

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