What would you think if you were told that you lived in a world with a large variety of humans—humans of all shapes and sizes that perform all different kinds of jobs that require varying skills and availability in time flow—how would you feel if you found out that everything in that world, despite all the variation, is specifically and intentionally designed to fit, suit and accommodate only one of those types? Everything, even down to the data that is collected about the whole, the data supposedly collected to display the variety, assumed to be inclusive of everyone?
What would you do if you found out that in this world even drugs, medicines, surgeries and medical devices are only tried out and accommodated to that same one type? What would you think if you learned that all the other types and varieties of humans are being prescribed and using the dosage based on the information gathered only on that other one type? What would you think if you learned that even testing for safety in automobiles, factories, workplaces and general public works, even those are also only measured by that same one type?
What would you think if you heard everything in that world is catered to that one type right down to the temperature of public spaces, the plowing of public streets, the design of living spaces, chairs, tables, couches, scissors, tools, and that everyone but this one type is considered an aberration and therefore left out of the equations?
This is, in fact, the reality that we are currently living. Everything is tailored to, built to, suited to, designed to, tested on men and it is a certain type of man. This is called the “male default.” And all the missing data is called the “gender data gap.”
“The history of humanity. The history of art, literature and music. The history of evolution itself. All have been presented to us as objective facts. But the reality is, these facts have been lying to us. They have all been distorted by a failure to account for half of humanity—not least by the very words we use to convey our half-truths. This failure has led to gaps in the data. A corruption in what we think we know about ourselves. It has fueled the myth of male universality. And that is a fact”(21).
Male default and the gender data gap are the two main themes in the book Invisible Women: Data Bias in a World Designed for Men by Caroline Criado Perez in which the author exposes this reality. It is shocking, enraging and often outrageously comical to read about. The book is chock-full of fact-based research, anecdotes, and examples of these issues as they play out in various cultures and different countries.
Fundamentally the book is asking for change and showing how that change can be accomplished. Fundamentally it would not be too hard. But we have to care about women to do it. We have to remember that women exist to do it. Yes, that is how deeply entrenched this issue is. Researchers, studies, data collectors literally forget that women exist and forget to ask women about the issue at hand when they carry out their studies and data collecting, even if it is an issue that mostly affects women.
This is not a book that is out to get or punish men. It’s not about that. This is a book that is casting a wide look at how our lives are designed and revealing how they are primarily designed for men. Whether intentional or not, it needs to stop. And we need to catch and stop this train before the bias infiltrates big tech further than it already has.
“Invisible Women is the story of what happens when we forget to account for half of humanity. It is an exposé of how the gender data gap harms women when life proceeds, more or less as normal. In urban planning, politics, the work place. It is also about what happens to women living in a world built on the 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. . . . 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”(25).
One of the best examples of how pervasive yet unnoticed this phenomena is lives in the story of snow-clearing in Karlskoga, Sweden in the chapter titled: “Can Snow-Clearing Be Sexist?”
In what started out as a joke, the town of Karlskoga Sweden under a gender-quality-initiative were investigating their policies through a gendered lens. A comment was made that at least they could be sure that snow-clearing was free from gender bias. And so, after a good laugh, the challenge was taken up and a study of snow-clearing and gender was undertaken. Shockingly, what it revealed is that indeed even snow-clearing is incredibly biased toward men. And why? Because of a lack of data on women and women’s lives.
In Karlskoga as in many other places the snow-clearing schedule began with the main arteries going into and out of the city center and ended with side streets and sidewalks assuming the main arteries are the most travelled and therefore take priority. But that turned out to only be true for men. The majority of women travel differently than men, and make up most of the users of pedestrian walkways, side streets and public transportation. And it turns out there are a lot of them needing to travel about early on snowy days.
“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”(30).
Upon viewing the data from the study, Karlskoga changed their snow clearing schedules and received an added, surprise benefit. Less people were getting injured on snowy days. It turned out that the emergency rooms were filled with mostly injured women on these days, women who had fallen on icy sidewalks and uncleared streets. Fixing this gender data gap actually saved the town money.
“The original snow-clearing schedule in Karlskoga hadn’t been deliberately designed to benefit men at the expense of women, Like many of the examples in this book, it came about as a result of a gender data gap— in this instance, a gap in perspective. The men (and it would have been men) who originally devised the schedule knew how they travelled and they designed around their needs. They didn’t deliberately set out to exclude women. They just didn’t think about them. They didn’t think to consider if women’s needs might be different. And so this data gap was a result of not involving women in the planning”(32).
With regard to studies of chemical exposure in workplaces on women, there is very little sex-disaggregated data and this is making a lot of women sick.
“We continue to rely on data from studies done on men as if they apply to women. Specifically, Caucasian men aged twenty-five to thirty, who weigh 70 kg. This is ‘Reference Man’ and his superpower is being able to represent humanity as a whole. Of course, he does not.
Men and women have different immune systems and different hormones, which can play a role in how chemicals are absorbed. Women tend to be smaller than men and have thinner skin, both of which can lower the level of toxins they can be safely exposed to. This lower tolerance threshold is compounded by women’s higher percentage of body fat, in which some chemicals can accumulate.
The result is that levels of radiation that are safe for Reference Man turn out to be anything but for women. Ditto for a whole range of commonly used chemicals. And yet the male-default-one-level-to-rule-them-all approach persists. This is made worse by the way chemicals are tested. To start with chemicals are still usually tested in isolation, and on the basis of a single exposure. But this is not how women tend to encounter them, either at home (in cleaning products and cosmetics), or in the workplace”(116-117).
Most of the data that we do have is misleading because it acts as though it is comprehensive when it is not, it acts as though it is inclusive when it is not. People make that assumption when reading the data. That is a wrong and misleading assumption which ends up being bad for women. We are applying male standards to women, standards for male bodies to female bodies which are inappropriate and could even be harmful.
“Even in industries with a good historical health and safety record women are still being failed. In the US, where by 2007 there were nearly 1 million female farm operators, ‘virtually all tools and equipment on the US market have been designed either for men or for some “average” user whose size, weight, strength etc. were heavily influenced by the average man’. This has led to tools that are too heavy or long; hand tools that are not appropriately sized or placed (women’s hands are on average 0.8 inches shorter than men’s); and mechanized equipment that is too heavy or that is difficult to control (for example pedals on tractors being placed too far from the seat)”(121).
“Wendy Davis, ex-director of the Women’s Design Service in the UK, questions the standard size of a bag of cement. It’s a comfortable weight for a man to lift – but it doesn’t actually have to be that size, she points out. ‘If they were a bit smaller then women could lift them.’ Davis also takes issue with the standard brick size. ‘I’ve got photographs of my [adult] daughter holding a brick. She can’t get her hand round it. But [her husband] Danny’s hand fits perfectly comfortably. Why does a brick have to be that size? It doesn’t have to be that size.’ She also notes that the typical A1 architect’s portfolio fits nicely under most men’s arms while most women’s arms don’t reach round it – and again has photos of her daughter and her husband to prove it”(122).
Piano keyboards are designed for men’s hands. Cell phones are sized for men’s hands. Voice recognition software is also male-biased. And “there has still been no biomechanics research of the effects of breast size on lifting techniques associated with back pain”(115).
No female crash test dummies. No accommodation in seat belts for breasts or pregnancy. All car models and seat models and therefore safety models based on men. Women suffer greater injury in crashes because of this. Why is it so hard to create a female crash test dummy? When they did attempted to create one, they only designed a smaller version of the male crash test dummy. In other words they still haven’t created one with breasts!
Another large issue exposed in the book is the issue of global unpaid female labor. These figures are literally not included in economic values and market evaluations. Meaning they have no market value and are not considered contributions to the economic reality of a country. Because it is disproportionately women who carry out all of this unpaid work and care, women themselves are devalued as well as their time and energy.
“The failure to measure unpaid household services is perhaps the greatest gender gap of all. Estimates suggest that unpaid care work could account for up to 50% of GDP in high-income countries and as much as 80% of GDP in low-income countries”(242).
This huge data gap keeps women poor, overworked and relegates what is considered “women’s work” to be less desirable and basically, invisible. The economic impact of this data gap on women’s lives is one thing but what about the cost to general health, mental health and self-esteem? Criado explores how this gap was intentionally created for the same reason so many of these kinds of data gaps are. The excuse is that women’s work patterns are just too complicated to research, record and include into the market values. Women’s lives, because they tend to be more involved with multi-tasking and various kinds of work in a 24 hour period including varying skills throughout that 24 hour interval, with multiple hours spent in multi-tasking situations, are deemed too complicated to take into consideration when gathering data that affects every part of our lives. Are women really that unimportant that such an excuse is actually accepted? It’s a travesty and it needs to stop.
The same excuse is made about women’s bodies as well, that women’s bodies are left out of health and other studies because women cycle and their bodies are therefore too complicated and that makes the research, testing and data collecting too difficult. As with ignoring women’s work patterns, this is a dangerous omission.
“We like to think that the unpaid work women do is just about individual women caring for their individual family members to their own individual benefit. It isn’t. Women’s unpaid work is work that society depends on, and it is work from which society as a whole benefits. When the government cuts public services that we all pay for with our taxes, demand for those services doesn’t suddenly cease. The work is simply transferred onto women, with all the attendant negative impacts on female paid labour-participation rate, and GDP. And so the unpaid work that women do isn’t simply a matter of ‘choice’. It is built into the system we have created—and it could just as easily be built out of it. We just need the will to start collecting the data, and then designing our economy around reality rather than a male-biased confection”(252-253).
Caroline Criado Perez is a #NastyWomanWriter and Activist
©Theresa C. Dintino 2021
Caroline Criado Perez. Invisible Women: Data Bias in a World Designed for Men. N.Y. Abrams Press, 2019.