Invisible Women: Exposing Data Bias in a World Designed for Men

by Caroline Criado Perez

  The violence nurses face at work is not helped by traditional hospital design. The long hallways isolate workers, explains Brophy, scattering them far away from each other. ‘Those hallways are terrible,’ one worker told Brophy. ‘You work way over there – and you can’t communicate. I would prefer a full roundabout circle.’ This would be an improvement, Brophy points out, because it would enable staff to support each other better. ‘If the area was rounded, workers wouldn’t be off on one end. If there was two people one would hear something going on.’ Most nursing stations don’t have protective shatterproof barriers or exits behind the desk, leaving nurses vulnerable to attack. Another worker told Brophy about the time her co-worker was sexually assaulted by a patient. ‘[Th]e inspector recommended that they put glass up. The hospital fought them on it. They said it stigmatises the patients.’

  Both the workers Brophy interviewed and the US’s Occupational Health and Safety Administration have highlighted several design features of traditional hospitals (‘unsecured access/egress; insufficient heating or cooling; irritating noise levels; unsecured items’) that compound the safety issue – all of which could be addressed without stigmatising anyone. Governments could also reverse policies that result in routine understaffing – an issue that Brophy ‘heard in every group in every location’, with workers identifying wait times as ‘a trigger’ for violent behaviour directed towards staff. ‘If you don’t have the staff to immediately address their issue – if they’re kept waiting – they are more likely to escalate in their behaviour,’ explained one worker.

  Redesigning hospital layouts and increasing staffing levels of course don’t come cheap – but there’s likely a cost argument that could be made given the amount of time off from injuries and stress workers are taking. Unfortunately, this data is not being ‘adequately collected’, Brophy tells me. But, he continues, ‘I can tell you there’s not a doubt in my mind that that is a very high stress work environment and that the demand on people and the limited amount of control they have is the perfect scenario for job burnout.’

  And then there’s the cost implications of training people who then leave the profession, which came up repeatedly in the focus groups the Brophys conducted. ‘We had nurses with twenty-five to thirty years’ seniority saying “I’m gonna become a cleaner,” or “I’m gonna work in the kitchen because I can’t deal with it any more. I can’t handle the lack of support and the danger and the risk and coming in every day and facing these things and then being negated and unsupported.”’

  But even without taking this more long-term view there are plenty of lower-cost options, some of them dazzlingly simple. Consistently charting and flagging patient violence; making reporting procedures less onerous – and having supervisors actually read the reports; ensuring alarms make different noises depending on their purpose: ‘[I]n one instance, the patient call bell, bathroom assist bell, Code Blue for respiratory or cardiac arrest, and staff emergency alarms all made the same sound in the nurse’s station’ (fans of British 1970s TV will recognise this problem with alarms as the plot of an actual Fawlty Towers episode).

  Signs making it clear what behaviour is and isn’t acceptable would also be inexpensive. ‘I notice at the hospital coffee shop they have a sign that says they won’t tolerate any type of verbal abuse,’ one woman told the Brophys. ‘But there’s no signs on our units that say that. [. . .] There is a poster about if you’re widowed and lonely, here’s a singles website. But you won’t put up a violence sign for us?’

  Perhaps most staggeringly simple, participants in the Brophys’ research ‘suggested that they be permitted to have their last names removed from their name tags – at their employer’s expense – as a safety measure’. This would avoid incidents such as when a visitor to the hospital told a female worker, ‘Very nice to meet you, [her name]. And you know, you shouldn’t have your last name on your badge because I can just look you up and find out who you are and where you live.’

  Women have always worked. They have worked unpaid, underpaid, underappreciated, and invisibly, but they have always worked. But the modern workplace does not work for women. From its location, to its hours, to its regulatory standards, it has been designed around the lives of men and it is no longer fit for purpose. The world of work needs a wholesale redesign – of its regulations, of its equipment, of its culture – and this redesign must be led by data on female bodies and female lives. We have to start recognising that the work women do is not an added extra, a bonus that we could do without: women’s work, paid and unpaid, is the backbone of our society and our economy. It’s about time we started valuing it.

  PART III

  Design

  CHAPTER 7

  The Plough Hypothesis

  It was the Danish economist Ester Boserup who first came up with the plough hypothesis: that societies that had historically used the plough would be less gender equal than those that hadn’t. The theory is based on the relative female-friendliness of shifting agriculture (which is done using handheld tools like hoes or digging sticks) versus plough agriculture (usually driven by a powerful animal like a horse or an ox), the idea being that the former is more accessible to women.1

  This sex difference in accessibility is partly because of the differences between male and female bodies. Ploughing requires ‘significant upper body strength, grip strength, and bursts of power, which are needed to either pull the plough or control the animal that pulls it,’ and this privileges male bodies.2 Upper-body mass is approximately 75%3 greater in men because women’s lean body mass tends to be less concentrated in their upper body,4 and, as a result, men’s upper body strength is on average between 40-60%5 higher than women’s (compared to lower-body strength which is on average only 25% higher in men6). Women also have on average a 41% lower grip strength than men,7 and this is not a sex difference that changes with age: the typical seventy-year-old man has a stronger handgrip than the average twenty-five-year-old woman.8 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.9 Overall, 90% of the women (this time including untrained women) in the study had a weaker grip than 95% of their male counterparts.

  But the disparity in the relative female-friendliness of plough versus shifting agriculture is also a result of gendered social roles. Hoeing can be easily started and stopped, meaning that it can be combined with childcare. The same cannot be said for a heavy tool drawn by a powerful animal. Hoeing is also labour intensive, whereas ploughing is capital intensive,10 and women are more likely to have access to time rather than money as a resource. As result, argued Boserup, where the plough was used, men dominated agriculture and this resulted in unequal societies in which men had the power and the privilege.

  According to a 2011 paper, Boserup’s hypothesis holds up to scrutiny.11 Researchers found that descendants of societies that traditionally practised plough agriculture held more sexist views even if they emigrated to other countries. The paper also found that sexist beliefs correlated with the kind of geo-climactic conditions that would favour plough agriculture over shifting agriculture. This suggested that it was the climate rather than pre-existing sexism that dictated the adoption of the plough – which in turn drove the adoption of sexist views.

  The plough theory has its detractors. A 2014 analysis of farming in Ethiopia points out that while farming is strongly identified with men in that country (the farmer is male in ‘virtually all Amharic folklore’), and ploughing in particular is exclusively male, the upper-body-strength argument doesn’t hold there, because they use a lighter plough (although this of course doesn’t deal with the capital investment or childcare issues).12 This analysis also cites a 1979 paper which disputes the theory on the basis that ‘even where the plough never was introduced, among South Cushites in particular, still men are th
e cultivators’.

  Are they though? It’s hard to say, because the data on who exactly is doing the farming is, yes, you’ve guessed it, full of gaps. You’ll find no end of reports, articles and briefing papers13 that include some variation on the claim that ‘women are responsible for 60-80% of the agricultural labour supplied on the continent of Africa’, but little in the way of evidence. This statistic has been traced back to a 1972 United Nations Economic Commission for Africa, and it’s not that it is necessarily wrong, it’s just that we can’t prove it one way or the other, because we lack the data.

  This is partly because, given men and women often farm together, it is difficult to accurately determine how much of the labour of either sex goes into producing an end food product. In a United Nations Food and Agriculture Organization (FAO) paper, economist Cheryl Doss points out that it also depends on how we define and value ‘food’: by caloric value (where staple crops would come out on top), or by monetary value (where coffee might win)? Given women ‘tend to be more heavily involved in the production of staple crops’, comparing calorific value ‘might indicate a significantly higher share being produced by women.’14

  ‘Might’ is doing a lot of work there, though, because national surveys often don’t report on whether farmers are men or women.15 Even where data is sex-disaggregated, careless survey design can lead to an under-reporting of female labour: if women are asked if they do ‘domestic duties’ or ‘work’, as if they are mutually exclusive (or as if domestic work is not work), they tend to just select ‘domestic duties’ because that describes the majority of what they do.16 This gap is then compounded by the tendency to ‘emphasize incomegenerating activities’, the result being that they often underestimate (often female-dominated) subsistence production. The censuses also tend to define agriculture as ‘field work’, which leads to an undercounting of the women’s work ‘such as rearing small livestock, kitchen gardening, and post-harvest processing’. It’s a fairly clear example of male bias leading to a substantial gender data gap.

  A similar problem arises with the division of work by researchers into ‘primary’ and ‘secondary’ activities. For a start, secondary activities are not always collected by surveys. Even when they are, they aren’t always counted in labour-force figures, and this is a male bias that makes women’s paid work invisible.17 Women will often list their paid work as their secondary activity, simply because their unpaid work takes up so much time, but that doesn’t mean that they aren’t spending a substantial proportion of their day on paid work. The result is that labour-force statistics often sport a substantial gender data gap.18

  This male bias is present in the data Doss uses to check the 60-80% statistics. Foss concludes that women make up less than half of the global agricultural labour force, but in the FAO data she uses, ‘an individual is reported as being in the agricultural labor force if he or she reports that agriculture is his or her main economic activity’. Which, as we’ve seen, is to exclude a substantial chunk of women’s paid labour. To be fair to Doss, she does acknowledge the issues associated with this approach, critiquing the absurdly low 16% reported share of the agricultural labour force for women in Latin America. Rural women in Latin America, notes Doss, ‘are likely to reply that “their home” is their primary responsibility, even if they are heavily engaged in agriculture’.

  But even if we were to address all these gender data gaps in calculating female agricultural labour we still wouldn’t know exactly how much of the food on your table is produced by women. And this is because female input doesn’t equal male output: women on the whole are less productive in agriculture than men. This doesn’t mean that they don’t work as hard. It means that for the work that they do, they produce less, because agriculture (from tools to scientific research, to development initiatives) has been designed around the needs of men. In fact, writes Doss, given women’s various constraints (lack of access to land, credit and new technologies as well as their unpaid work responsibilities) ‘it would be surprising if they were able to produce over half of food crops’.

  The FAO estimates that if women had the same access to productive resources as men, yields on their farms could increase by up to 30%.19 But they don’t. In an echo of the introduction of the plough, some modern ‘labour-saving’ devices might more precisely be labelled ‘male labour-saving’ devices. A 2014 study in Syria, for example, found while the introduction of mechanisation in farming did reduce demand for male labour, freeing men up to ‘pursue better-paying opportunities outside of agriculture’, it actually increased demand ‘for women’s labour-intensive tasks such as transplanting, weeding, harvesting and processing’.20 Conversely, when some agricultural tasks were mechanised in Turkey, women’s participation in the agricultural labour force decreased, ‘because of men’s appropriation of machinery’, and because women were reluctant to adopt it. This was in part due to lack of education and sociocultural norms, but also ‘because the machinery was not designed for use by women’.21

  It’s not just physical tools that can benefit men at the expense of women. Take what are called ‘extension services’ (educational programmes designed to teach farmers science-based practice so they can be more productive). Historically, extension services have not been female-friendly. According to a 1988-9 FAO survey (limited to those countries that actually had sex-disaggregated data) only 5% of all extension services were directed towards women.22 And while things have slightly improved since then,23 there are still plenty of contemporary examples of development initiatives that forget to include women24 – and therefore at best don’t help, and at worst actively disadvantage them.

  A 2015 analysis by Data2x (a UN-backed organisation set up by Hillary Clinton that is lobbying to close the global gender data gap) found that many interventions simply don’t reach women in part because women are already overworked and don’t have time to spare for educational initiatives, no matter how beneficial they may end up being.25 Development planners also have to factor in women’s (lack of) mobility, in part because of their care responsibilities, but also because they are less likely to have access to transport and often face barriers to travelling alone.

  Then there’s the language and literacy barrier: many programmes are conducted in the national language, which women are less likely than men to have been taught. Due to the low global levels of female education, women are also less likely to be able to read, so written materials don’t help either. These are all fairly basic concerns and shouldn’t be hard to account for, but there is plenty of evidence that they continue to be ignored.26

  Many development initiatives exclude women by requiring a minimum land size, or that the person who attends the training is the head of a farming household, or the owner of the land that is farmed. Others exclude women by focusing solely on farms that have enough money to be able to purchase technology, for example. These conditions are all biased towards male farmers because women dominate the ranks of poor farmers, they dominate the ranks of small-scale farmers, and they are overwhelmingly unlikely to own the land that they farm.27

  In order to design interventions that actually help women, first we need the data. But it sometimes feels like we’re not even trying to collect it. A 2012 Gates Foundation document tells the story of an unnamed organisation that aimed to breed and distribute improved varieties of staple crops.28 But ‘improved’ is in the eye of the farmer, and when this organisation did its field-testing it spoke almost exclusively to men. Male farmers said that yield was the most important trait, and so that was the crop that the organisation bred. And then it was surprised when households didn’t adopt it.

  The decision to talk only to men was bizarre. For all the gaps in our data we can at least say that women do a fair amount of farming: 79% of economically active women in the least developed countries, and 48% of economically active women in the world, report agriculture as their primary economic activity.29 And the female farmers in this area didn’t see yields as the most important
thing. They cared about other factors like how much land preparation and weeding these crops required, because these are female jobs. And they cared about how long, ultimately, the crops would take to cook (another female job). The new, high-yield varieties increased the time the women had to spend on these other tasks, and so, unsurprisingly, they did not adopt these crops.

  The only thing that development planners need to do to avoid such pitfalls is speak to some women, but they seem bafflingly resistant to this idea. And if you think the decision to design a new staple crop without talking to women is bad, wait until you hear about the history of ‘clean’ stoves in the developing world.

  Humans (by which I mean mainly women) have been cooking with three-stone fires since the Neolithic era. These are exactly what they sound like: three stones on the ground on which to balance a pot, with fuel (wood or whatever else you can gather that will burn) placed in the middle. In South Asia, 75% of families are still using biomass fuels (wood and other organic matter) for energy;30 in Bangladesh, the figure is as high as 90%.31 In sub-Saharan Africa biomass fuels are the primary source of energy used for cooking for 753 million people.32 That’s 80% of the population.

  The trouble with traditional stoves is that they give off extremely toxic fumes. A woman cooking on a traditional stove in an unventilated room is exposed to the equivalent of more than a hundred cigarettes a day.33 According to a 2016 paper, in countries from Peru to Nigeria, toxic fumes from stoves are between twenty and a hundred times above World Health Organization guideline limits,34 and globally they cause three times more deaths (2.9 million)35 every year than malaria.36 This is all made worse by the inefficiency of traditional stoves: women who cook on them are exposed to these fumes for three to seven hours a day,37 meaning that, worldwide, indoor air pollution is the single largest environmental risk factor for female mortality and the leading killer of children under the age of five.38 Indoor air pollution is also the eighth-leading contributor to the overall global disease burden, causing respiratory and cardiovascular damage, as well as increased susceptibility to infectious illnesses such as tuberculosis and lung cancer.39 However, as is so often the case with health problems that mainly affect women, ‘these adverse health effects have not been studied in an integrated and scientifically rigorous manner’.40