Virginia Hart

The evolution and history of humanity is the story shaped by the absent present of women. Whether it is in films, literature, science, or medicine – women are silenced and the lives of half of humanity therefore are left unspoken, unseen and inexistent.

It is not a new observation that women are mostly left unseen. Though it became most famously outspoken when Simone de Beauvoir wrote: “Humanity is male and man defines woman not in herself, but as relative to him; she is not regarded as an autonomous being. […] He is the Subject; he is the Absolute – she is the Other” . In a modern context where a lot of importance is given to data it becomes not only a silencing of women but also an even more concerning danger to the female existence. This doesn’t mean being a woman is a life-threatening birth right, but it means women are part of a system which is built upon data in which they are not represented. Looking into examples makes it clear this data gap has larger consequences and impacts women’s everyday lives.

masculine defaults
There are different explanations why women are forgotten and underrepresented in data. Most of them probably are not deliberate but are the product of the way of thinking that has been around, reproduced and conserved over the past millennia. One of these explanations is the misperception when we speak of humans, we’re often only addressing men. This means that when something is defined as standard, normal or neutral for humans it actually most often only applies to male but not female behavior and characteristics. Therefore, it is not neutral. This is what can be described as the masculine default and the consequences can be lethal. As an example; safety measurements in cars are not applied to females because safety simulations were done with dummies with standard norms which only represent the male anatomy and physique. This leads to females being more likely than males to be killed or injured in car crashes of equal severity.

Another example, swedish hospitalization statistics have shown that almost 90% of pedestrian injuries in winter happened because of slipping and falling on snowy or icy paths occur to women. And this most certainly isn’t because women are clumsier. It is because women and men travel differently, and this isn’t being considered when snow-cleaning is organized and carried out. When it comes to snow cleaning in cities it is the same for most countries. First (main) roads for cars and public transport are cleared, then some bicycle routes and lastly pedestrian pathways. But most often a lot of pedestrian pathways are not properly cleaned leading to slippery pathways. The logic behind the order might be that the cleaning necessity should correlate with the severity of a possible injury. And when comparing a car accident to a pedestrian falling, it seems clear that the urgency to clean roads is bigger than it is to clean pathways. Additionally, the majority of people planning and working in this area are male. And it is statistically proven that men more often go to work by car than by foot. Leading to the generall assumption that everyone mostly goes to work by car. This doesn’t mean that men intentionally choose roads over pathways but if men perceive their way of mobility (going by car) as normal, women are being unintentionally left unconsidered. Looking at futher statistics it has become clear that men and women have different daily lives with different usage of mobility. As the majority of care-work is done by women, it influences their daily life a lot. It leads to women having daily routes with several stops during the day whereas men mostly go from home to work (to the gym) and back again. Women are more likely to be the ones that take their kids to school before going to work. They are also more likely to do household work which involves grocery shopping which leads to another stop on their way home before picking up their kids again. As you see our daily lives are influenced by the cultural tasks that have been assigned to gender. Most of these tasks are done on foot explaining why women are more likely to be the ones that use footpaths and therefore are more likely to get injured when pathways are not cleared as thoroughly as streets are. In an attempt of change, a swedish city increased the cleaning of pathways and as a result the rate of pedestrians (women) being injured and hospitalisations dropped immensely.

An illustration of the influence of gender addressed work influences daily life activity and mobility
Source: https://www.iass-potsdam.de/de/blog/2021/06/frauen-gender-und-mobilitaet

equality benefits all
The examples above show how masculine default pretends to be equal but fails. But they also only highlight how women suffer from it and that a change will come to the benefit of women.
In fact, often when we speak of achieving gender equality it is about creating equal chances for women. Which may sound like the benefit is just for women. When you believe men and women are already equal you might see those attempts of gender equality as a threat. Or that supporting women comes with a disadvantage for men. But equality for women also benefits men. It benefits all. In the second example we saw that changing snow-clearing habits to the benefit of pedestrians resulted a decrease in women getting insured. But changing showed additional effects nobody had thought of in the first place. Namely, the high amount of injuries cost a lot of money for healthcare and therefore productivity is lost. By decreasing those injuries, a lot of money was saved. This comes to the benefit of all. As well if women were injured, they could not go to work and this would lead to higher costs and a loss of productivity for employers. With women being unable while injured to do their usual carework, husbands were left to it and had to take off work which meant their employer lost productivity as well. Due to the decrease of injured women this money was saved to the benefits of the economy. Which proves that benefiting women, benefits everyone, even from an economic perspective.

References:

Anke Kläver. „Frauen, Gender und Mobilität“, o. J. https://www.iass-potsdam.de/de/blog/2021/06/frauen-gender-und-mobilitaet.

Criado-Perez, Caroline. Invisible Women: Exposing Data Bias in a World Designed for Men. London: Vintage, 2020.

Sapna Cheryan, Hazel Rose Markus. „Supplemental Material for Masculine Defaults: Identifying and Mitigating Hidden Cultural Biases“. Psychological Review, 2020, rev0000209.supp. https://doi.org/10.1037/rev0000209.supp.

Beauvoir, Simone de, Constance Borde, Sheila Rowbotham, und Simone de Beauvoir. The Second Sex. London: Vintage, 2011.