Measuring scientific influence
Claire Cain Miller (2007), in Forbes, reports that gender diversity in R&D may not just be good for people, but good for companies and science in general. "Who Invents IT?", a report released this week by the National Center for Women & Information Technology, examines the relationship between IT patent-holder gender and the number of times that patent is cited in subsequent patents. NCWIT found that mixed-gender patents received up to 42% more citations than single-gender patents. Women were named on only 6.1% of U.S. IT patents in 2005.
The underrepresentation of women in patenting is not unique to the IT field. Ding et al (2006) found that academic women in the life sciences applied for patents only 40% as much as their male peers. Robert Fisher (2005) suggests that women may choose less risky research subjects, leading to fewer patentable breakthroughs. However, Ding's study, which also used "number of citations" as a measure for the influence of research, found that women's papers were cited slightly more often than men's (there is no detail as to mixed-gender groups provided). Ding suggests that concern about maintaining their academic careers is a higher priority for women scientists, which they choose not to jeopardize by pursuing commercial ventures.
How do you measure the scientific impact of an idea? The number of citations seems like as good a place as any to start, but I wonder how much the politics of citing comes into play. Most of the scientists I know are fairly cynical about the business of publication in general, and about citations in particular. Still, I find it extremely promising to see results-based arguments about women's inclusion in science, rather than morally based ones. If mixed-gender teams are coming up with more influential work, that seems like the best reason to keep both men and women involved in science (and everything else, for that matter). Even after more than a year of researching for Difference Blog, I'm hesitant to say I could quantify the differences in the way men and women think -- but I do believe that there is one, and that it has an effect on the way they solve problems.
The underrepresentation of women in patenting is not unique to the IT field. Ding et al (2006) found that academic women in the life sciences applied for patents only 40% as much as their male peers. Robert Fisher (2005) suggests that women may choose less risky research subjects, leading to fewer patentable breakthroughs. However, Ding's study, which also used "number of citations" as a measure for the influence of research, found that women's papers were cited slightly more often than men's (there is no detail as to mixed-gender groups provided). Ding suggests that concern about maintaining their academic careers is a higher priority for women scientists, which they choose not to jeopardize by pursuing commercial ventures.
How do you measure the scientific impact of an idea? The number of citations seems like as good a place as any to start, but I wonder how much the politics of citing comes into play. Most of the scientists I know are fairly cynical about the business of publication in general, and about citations in particular. Still, I find it extremely promising to see results-based arguments about women's inclusion in science, rather than morally based ones. If mixed-gender teams are coming up with more influential work, that seems like the best reason to keep both men and women involved in science (and everything else, for that matter). Even after more than a year of researching for Difference Blog, I'm hesitant to say I could quantify the differences in the way men and women think -- but I do believe that there is one, and that it has an effect on the way they solve problems.