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Women are still considered second, and you may not understand how it is done. Some obvious: Women earn less than men and have fewer leadership positions in organizations and boards. As a result of the epidemic, women’s career paths were also significantly sidetracked (or ended) at a rate not seen in the case of men’s career paths. Women’s perspectives and experiences are downplayed, and this contributes to gender bias and gender gaps. Their needs are met and / or masked by the male needs or wants.
In a lesser known way this inequality occurs through information. You may be saying, “How can this be? Based on data research and information. How can information that is biased actually Creates?The answer involves contempt for women in research – from business to technology to medicine and other practical aspects of life.
What is data bias?
Data is collected to provide evidence of what works (or doesn’t work) for different projects, ideas or innovations. This allows researchers to figure out what to adjust and / or move forward. One variable in the research that makes the investigation challenging is the breadth: all aspects of data application need to be considered. When one aspect is ignored, there can be negative or dangerous consequences. Consider, for example, the killing of a woman in Arizona by a self-propelled Uber car. Uber has determined that the car cannot detect that an object was a pedestrian unless it was near a crosswalk – a surveillance that creates a dangerous data bias.
Also consider facial recognition software, a tool used by many law enforcement agencies. After applying it to identify, target, and convict criminals, research has shown that in many cases its algorithms were significantly less accurate when it comes to people of color as well as women. As a result, bias had a profound effect on both civil rights and public security.
In the process of designing research and data collection, researchers rely on a sample population – meaning to represent the larger population to which research results and other data will be applied. But in order to be effective, that sample must include all sectors of the larger population. In the case of gender information bias, women are ignored.
Related: How entrepreneurs can conduct initial market research
What is gender information bias?
In many cases of research, female samples are not included in a fair percentage of the population, if at all. This may be true if the information is not applied to women, but it is. Products, services and strategies are being generalized to women when the research behind them is not based on data. Involved Women read this again: something is being done and used by women and we don’t know if it works for them or is safe for them. Consider these examples:
Women’s hands are usually shorter than men’s (about one to two inches), but this is not usually considered when designing a cell phone. These are now virtually indispensable tools – and especially a trend towards their ever-increasing size – no matter how small a phone fits. Although some companies offer smaller models, they usually offer less powerful or lesser options. Another example involves Google Home: the speech recognition databases used to create this application – sociologist and data scientist Dr. According to a 2016 study by Rachel Tatman – the male voice was dominant, which made it 70% more likely to recognize and respond effectively. Men’s voices over women.
Women are more likely to die of a heart attack because their symptoms are often considered “atypical”. This is because the study identified standard symptoms that focused on the presentation of men (chest pain, left hand pain) versus women (shortness of breath, nausea, fatigue, abdominal pain). Collectively, this bias is often referred to as The Yantile Syndrome, and was detailed in a 2011 article. European Heart Journal. This makes the male body the default for medical understanding and this is also true of medical research, where about 85% of the rats used in the experiment were male, according to a 2011 report. Neuroscience and biological behavioral reviews Articles
Women are more likely to be seriously injured in a car accident. Why? This is because automobile manufacturers have a “standard seating position” that is used for safety research based on men’s dimensions. Women are usually shorter than men, and therefore have to sit near the steering wheel to see clearly, but this information is not included in the manufacturers’ “standards”. Women are also more likely to die in a car accident due to similar gender data bias. Male crash-test dummies are commonly used to test the driver’s seat. When female crash-test dummies are used, they are usually confined to the passenger seat. The result is that existing research is not accurate or applicable to female drivers.
In some countries, female officers wear clothes designed and researched for men’s bodies, making them more vulnerable and less secure than their male counterparts. A 2017 Trade Union Congress report detailed these inequalities in the British PPE application, and many of the same issues apply equally to the United States.
Related: Labeled women and workplace bias
Published by research Nature Climate change Explained in 2015 how workplace temperatures affect productivity and similarly show gender data bias. As a woman, if you are wondering why you are always cold at work when your male colleagues are comfortable, the reason is that physiological differences are not considered when researching the ideal temperature for employee productivity and comfort. Research has a tendency to use male physiology as a standard, which is not responsible for body mass index or gender differences in overall body composition. And from a clothing standpoint, men generally tend to wear more suits and layers as part of office attire, where women don’t. If not considered part of the research on office climate, women fall into a dilemma.
This field of study and its application is generally influenced by men and is often confined to their perspectives: data relating to women are largely ignored. Subways, for example, are built for efficiency and affordability, and dim lighting and uninhabited areas are more common than monitored areas. This puts women at a significant disadvantage, creating areas where they are more likely to be attacked and / or harassed. Also, suburbs are still planned using an old-fashioned approach as the man’s earner and with an emphasis on daily commuting skills (according to our 2021 Secure Future article). This makes the management of household chores (including work and child care) more challenging and that important work often falls under the responsibility of women.
How, you might ask, could this be a massive neglect for data in many areas of life? The answer is simple and the catch-22 of this situation is: women are considered second, which means they don’t even think about when the research is conducted, which then contributes. More Women are considered second. It is also costly to create more comprehensive (or multiple) research studies needed to capture all potential customers connected to the data. This cyclical pattern maintains the status of women as invisible or irrelevant and binds them to a dominant, controlled or occupying male structure in their lives and activities.
Related: 4 Mistakes We all make to perpetuate gender bias
What can we do?
The solution to these problems, regardless of our role or gender, begins with better demands. We To be able to This data influences decisions that affect bias through actions and choices.
As members of society, we can become critical analysts of information, including asking and / or researching how data is collected. Create questions about who is included in the sample population and whether the people to whom the data is being applied are fairly represented. If they don’t, ask research and challenge businesses without investing your money in their products.
As a leader, consider your teams carefully – especially when creating research, collecting data, or using data. Are they diverse, not just their technical and professional skills, but who they are? Do they represent the population that the data will be applied to? Do they need a more diverse and representative perspective? As a leader, you can also create a professional culture that encourages individuals to challenge protocols and data. Having similarities in group and group discussions is not always ideal, as it does not allow for new perspectives and does not encourage sharing of concerns.
As women, we can use our money to influence change. Women are estimated to account for 70% to 80% of all consumer purchases, yet many companies continue to use biased data towards men to market to men or emphasize their preferences. Women may refuse to give their money to companies that do not embrace equality in research protocols; Otherwise, there will be little motivation to change them.
Related: That’s why we still need women’s networking groups
Ignoring gender data bias contributes to and facilitates the placement of women as secondary in our world. Beginning to progress as a society and as a woman recognizes how representative research and data can equalize the playing fields. When we can make it happen, we affect women in the present and in the future and in all areas of life.