This article, "Bias Called Persistent Hurdle for Women in Sciences", was published in the New York Times just a few days ago. Although it does not deal directly with bias in writing, it addresses bias on a broader scale: that careers in math and science are dominated overwhelmingly by men. The bias that men are inherently better at some subjects than women is expressed through language, whether spoken, written or implied.
As this article explains, a report by the American Association of University Women demonstrated that the gap is closing between genders, but bias is still prevalent in the sciences. They conducted studies where the actual act of telling women that they aren't expected to do as well as men on a math exercise may have provoked that very result. The women in the study had comparable backgrounds and abilities in math to those of the men. The difference in the control where women weren't told this was minimal: women scored 17 and men scored 19. However, the scores varied tremendously when the women were told that they weren't expected to score as well: women scored 5 and men scored 25. The research suggested that women may be less likely than men to pursue fields in math and sciences as a reaction to this belief that they will not be as successful in these pursuits.
These findings show how great of an impact stereotypical language can have on performance. This reminded me of the comment of the politician in my article on the Canadian national anthem yesterday stating, "There’s lots of things to do for women more important than changing the words of the national anthem." This research suggests that if we continue to use sexist language that discrepancies in achievement will be reinforced. A positive finding in this article is when women are in fact aware of such bias the effect that the bias has on performance is diminished, which is why it is important to explore these topics in an academic setting like we are doing in class.
Link to Article Below:
http://www.nytimes.com/2010/03/22/science/22women.html?ref=science
Tuesday, March 23, 2010
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