Gender bias in science

From Simple English Wikipedia, the free encyclopedia

Gender bias is a set of words used in social science. Gender bias is when scientific studies are biased, or slanted, towards one gender. Studies with gender bias do not represent the true gender balance.[1]

Gender bias has many causes:

  • Using gender stereotypes, rather than checking the true role: Tools that doctors use to identify some mental illnesses (such as clinical depression or ADHD) often use stereotyped gender roles. For example, in girls, being hyperactive is often seen as good thing. People think that girls are supposed to talk and smile a lot. In boys, being hyperactive is seen as a weakness. For another example, in many societies in which men are in charge, men are often seen as normal, and no one questions or thinks about this much. This makes an androcentric view, which is biased towards men.
  • Failure to take gender-specific factors into account. For example, when scientists study clinical depression again, sometimes they think that clinical depression is naturally more common in women than in men. However, women tend to ask for professional help with depression sooner than men do. Men are more likely to hide their problems. This is because boys learn not to ask for help. So depression might not be as much more common in women than it looked like at first. There may be similar gender bias with ADHD. The fact that men and women are fundamentally different is not taken into account. For this reason, in the case of ADHD, doctors see men as having a problem sooner than they see women as having a problem. This also affects the gender pay gap.[2]
  • Gender-specific language: Many languages use the male form for both sexes. Sometimes, readers think the writer is talking about everyone when the writer really is only talking about men and boys. However, saying that someone "has a full-time job" may introduce a bias: In most cultures in the world where there are "traditional role models," women do rarely have full-time jobs, especially when they also look after their children.
  • Overgeneralizations: Generalizing results that only affect one gender to all. Many drugs are only tested on men and women do not take them until they are approved for use in patients. Such drugs may not work the same way on women; certain drugs may be dangerous for women (that's why they need to be tested on women as well)

References[change | change source]

  1. Sabine Girod, Magali Fassiotto et al.: Reducing Implicit Gender Leadership Bias in Academic Medicine With an Educational Intervention. In: Academic Medicine. Vol.91, issue 8, August 2016, pp. 1143–1150
  2. Claudia Finke: Verdienstunterschiede zwischen Männern und Frauen: Eine Ursachenanalyse auf Grundlage der Verdienststrukturerhebung 2006. Statistisches Bundesamt, Wiesbaden Januar 2011, pp- 36–48, this reference on p. 45 (PDF: 1,9 MB, 161 pages on