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Bias: How people of science view minorities
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The data gap is often used as an example to prove that women today live with the consequences of bias from the past. People today live in extreme poverty, are overlooked for jobs and are paid less for the jobs they do have because of unconscious bias. Unconscious bias applies stereotypes onto different groups of people, harming their image and their chance at equal opportunities.There is gap in data and diverse personnel in governments, science and positions of power, and this gap has the potential to be dangerous. In this presentation I will be highlighting a proposed experiment that could test how the science faculty’s bias affects women, ethnic minorities, and women of ethnic minorities, all in comparison to the majority candidate (white, male, white male). I used hypothesis data that I made up in sample sizes of 150 to provide figures for the presentation based on the data from a real experiment in (Eaton et al., 2019). The results show that women are seen as less competent than men, and that Black and Middle Eastern students are seen as less competent than White and Chinese students. Combining the results it is seen that Black women and Middle Eastern men are seen as the least competent than any other group, in comparison to White and Chinese males which are seen as the most competent. This data is then linked to factors such as the distribution of privilege and the social ladder. The presentation offers ways in which people can reduce their bias by awareness, bias training, discussion and empathy.
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- Date created
- 2021-08-16
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- Type of Item
- Conference/Workshop Poster