Invisible Women Quotes

“for the vast majority of hiring decisions around the world, meritocracy is an insidious myth. It is a myth that provides cover to institutional white male bias.”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“The implicit bias is clear: expense codes are based on the assumption that the employee has a wife at home taking care of the home and the kids. This work doesn’t need paying for, because it’s women’s work, and women don’t get paid for it.”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“professors hired at the top fifty US economics departments between 1985 and 2004 found that the policies ultimately led to a 22% decline in women’s chances of gaining tenure at their first job. Meanwhile men’s chances increased by 19%.”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“When Google noticed that they were losing women who had just given birth at twice the rate of other employees, they increased their maternity leave from three months at partial pay to five months at full pay. The attrition rate dropped 50%.66”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“UC Berkeley Rodolfo Mendoza-Denton has a cognitive explanation for why we may view Clinton’s ambition as ‘pathological’.15 She ‘was forging into a territory that is overwhelmingly associated in people’s minds with men’. As a result, he explains, voters experienced her candidacy as a norm violation. And norm violations are, Mendoza-Denton writes, ‘quite simply, aversive, and are often associated with strong negative emotion’.”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“When things go wrong – war, natural disaster, pandemic – all the usual data gaps we have seen everywhere from urban planning to medical care are magnified and multiplied. But it’s more insidious than the usual problem of simply forgetting to include women. Because if we are reticent to include women’s perspectives and address women’s needs when things are going well, there’s something about the context of disaster, of chaos, of social breakdown, that makes old prejudices seem more justified. And we’re always ready with an excuse. We need to focus on rebuilding the economy (as we’ve seen, this is based on a false premise). We need to focus on saving lives (as we will see this is also based on false premise). But the truth is, these excuses won’t wash. The real reason we exclude women is because we see the rights of 50% of the population as a minority interest.”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“Female homelessness is therefore not simply a result of violence: it is a lead predictor of a woman experiencing violence”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“This may be partly because women are ‘better suited for leadership than men’.10 That was the conclusion of a study conducted by BI Norwegian Business School, which identified the five key traits (emotional stability, extraversion, openness to new experiences, agreeableness and conscientiousness) of a successful leader. Women scored higher than men in four out of the five.”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“For example, quotas, which, contrary to popular misconception, were recently found by a London School of Economics study to ‘weed out incompetent men’ rather than promote unqualified women.71”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“Identity is a potent force that we ignore and misread at our peril: Trump, Brexit and ISIS (to name just three recent examples) are global phenomena that have upended the world order – and they are all, at heart, identity-driven projects.”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“Women are also asked to do more undervalued admin work than their male colleagues32 – and they say yes, because they are penalised for being ‘unlikeable’ if they say no.”
― Caroline Criado Pérez, Invisible Women: Exposing Data Bias in a World Designed for Men

“historiadora Laurel Thatcher Ulrich, «las mujeres que se portan bien casi nunca hacen historia».”
― Caroline Criado Pérez, La mujer invisible: Descubre cómo los datos configuran un mundo hecho por y para los hombres

“La valía es una cuestión de opinión, y la opinión está basada en la cultura. Si esta cultura tiene un sesgo masculino muy marcado, como en la nuestra, no podrá evitar estar sesgada contra las mujeres. Por defecto.”
― Caroline Criado Pérez, La mujer invisible: Descubre cómo los datos configuran un mundo hecho por y para los hombres

“expense codes are based on the assumption that the employee has a wife at home taking care of the home and the kids.”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“All ‘people’ needed to do was to ask women.”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“Closing the data gap, as we’ve seen from the impact women have in politics, in peace talks, in design and urban planning, is good for everyone. Even mathematicians.”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“Boulanger is not a one-off. Women working as carers and cleaners can lift more in a shift than a construction worker or a miner.”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“By accounting for the sexual violence women face and introducing preventative measures – like providing enough single-sex public toilets – we save money in the long run by reducing the significant economic cost of violence against women. When we account for female socialisation in the design of our open spaces and public activities, we again save money in the long run by ensuring women’s long-term mental and physical health.”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“And when we don’t collect and, crucially, use sex-disaggregated data in urban design, we find unintended male bias cropping up in the most surprising of places.”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“Come on now,’ she chided in a column. ‘You’ve played games as a blue hedgehog. As a cybernetically augmented space marine. As a sodding dragon-tamer. [. . .B]ut the idea that women can be protagonists with an inner life and an active nature is somehow beyond your imaginative capacities?”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“Let’s start with the assumption that all members of a household enjoy an equal standard of living. Measuring poverty by household means that we lack individual level data, but in the late 1970s, the UK government inadvertently created a handy natural experiment that allowed researchers to test the assumption using a proxy measure.16 Until 1977, child benefit in Britain was mainly credited to the father in the form of a tax reduction on his salary. After 1977 this tax deduction was replaced by a cash payment to the mother, representing a substantial redistribution of income from men to women. If money were shared equally within households, this transfer of income ‘from wallet to purse’ should have had no impact on how the money was spent. But it did. Using the proxy measure of how much Britain was spending on clothes, the researchers found that following the policy change the country saw ‘a substantial increase in spending on women’s and children’s clothing, relative to men’s clothing’.”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“Transferring childcare from a mainly unpaid feminised and invisible form of labour to the formal paid workplace is a virtuous circle: an increase of 300,000 more women with children under five working full-time would raise an estimated additional £1.5 billion in tax.84 The WBG estimates that the increased tax revenue (together with the reduced spending on social security benefits) would recoup between 95% and 89% of the annual childcare investment.85 This is likely to be a conservative estimate, because it’s based on current wages – and like properly paid paternity leave, publicly funded childcare has also been shown to lower the gender pay gap. In Denmark where all children are entitled to a full-time childcare place from the age of twenty-six weeks to six years, the gender wage gap in 2012 was around 7%, and had been falling for years. In the US, where childcare is not publicly provided until age five in most places, the pay gap in 2012 was almost double this and has stalled.”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“At least one US psychiatric textbook, still widely in use during the 1970s, recommended lobotomies for women in abusive relationships.62”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“When Apple launched its health-monitoring system with much fanfare in 2014, it boasted a ‘comprehensive’ health tracker.15 It could track blood pressure; steps taken; blood alcohol level; even molybdenum (nope, me neither) and copper intake. But as many women pointed out at the time, they forgot one crucial detail: a period tracker.16”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“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”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“Until 2013, when three RAF recruits (one of whom had been medically discharged after suffering four pelvic fractures45), challenged the practice in court, women in the British armed forces were forced to match male stride length (the average man’s stride is 9-10% longer than the average woman’s).46 Since the Australian Army reduced the required stride length for women from thirty inches to twenty-eight inches, pelvic stress fractures in women have fallen in number.”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“Recent research has emerged showing that while women tend to assess their intelligence accurately, men of average intelligence think they are more intelligent than two-thirds of people. This being the case, perhaps it wasn’t that women’s rates of putting themselves up for promotion were too low. Perhaps it was that men’s were too high.”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“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.”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“It’s tempting to think that the male bias that is embedded in language is simply a relic of more regressive times, but the evidence does not point that way. The world’s ‘fastest-growing language’,34 used by more than 90% of the world’s online population, is emoji.35 This language originated in Japan in the 1980s and women are its heaviest users:36 78% of women versus 60% of men frequently use emoji.37 And yet, until 2016, the world of emojis was curiously male. The emojis we have on our smartphones are chosen by the rather grand-sounding ‘Unicode Consortium’, a Silicon Valley-based group of organisations that work together to ensure universal, international software standards. If Unicode decides a particular emoji (say ‘spy’) should be added to the current stable, they will decide on the code that should be used. Each phone manufacturer (or platform such as Twitter and Facebook) will then design their own interpretation of what a ‘spy’ looks like. But they will all use the same code, so that when users communicate between different platforms, they are broadly all saying the same thing. An emoji face with heart eyes is an emoji face with heart eyes. Unicode has not historically specified the gender for most emoji characters. The emoji that most platforms originally represented as a man running, was not called ‘man running’. It was just called ‘runner’. Similarly the original emoji for police officer was described by Unicode as ‘police officer’, not ‘policeman’. It was the individual platforms that all interpreted these gender-neutral terms as male. In 2016, Unicode decided to do something about this. Abandoning their previously ‘neutral’ gender stance, they decided to explicitly gender all emojis that depicted people.38 So instead of ‘runner’ which had been universally represented as ‘male runner’, Unicode issued code for explicitly male runner and explicitly female runner. Male and female options now exist for all professions and athletes. It’s a small victory, but a significant one.”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“In Katebe, a town in central Uganda, the World Bank found that after spending nearly fifteen hours on a combination of housework, childcare, digging, preparing food, collecting fuel and water, women were unsurprisingly left with only around thirty minutes of leisure time per day.44 By contrast, men, who spent an hour less than women per day digging, negligible amounts of time on housework and childcare, and no time at all on collecting fuel and water, managed to find about four hours per day to spend on leisure. The home may have been a place of leisure for him – but for her? Not so much.”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men