Needing data for your latest presentation on faculty women in STEM? Check out this fabulous graphical tool by the Chronicle of Higher Education for looking at racial-ethnicity/gender demography among tenure-track faculty in US. http://chronicle.com/
Check out this amazing project and video: Living Thinkers: An Autobiography of Black Women in the Ivory Tower.
The template integrates data from 5 national and local sources:
- Ph.D. Pipelines data: NSF Survey of Earned Doctorates, (2012) https://ncsesdata.nsf.ov/webcaspar/
- Postdoc pipeline data: Survey of Graduate Students & Postdocs (2012) https://ncsesdata.nsf.gov/webcaspar/
- Department Peer Data: AAU Data Exchange obtained from the university’s Office of Institutional Assessment or similar office
- School & Department Data: Obtained from the university’s Office of Institutional Assessment or similar office
- Applicant Data: Obtained from the university’s Office of Human Resources
Data entered into the “raw data template,” will generate a gender by race data table, along with graphs depicting the data by gender, and gender by race for the academic department of interest.
At our next AIM Network meeting (Oct. 13th, 2015; 11:30 am ET), Dr. Kelly Feltault, U.Va. CHARGE Program Manager, will demonstrate how to use the template. AIM Network members and guests will have the opportunity to share faculty recruitment tools they are using, and discuss considerations for using the proposed template at their institutions. JOIN US!
If you are interested in participating, please send a request to advanceAIMnetwork@gmail.com.
Kudos to Korman and AIM Network colleague, Goodwin, for their recent In Mind Blog post in response to Williams and Ceci’s (2015) Proceedings from the National Academy of Science publication entitled, “National Hiring Experiments Reveal 2:1 Faculty Preference for Women in STEM Tenure Track.“
Korman and Goodwin (2015) note:
By presenting lifestyle information explicitly, Williams and Ceci (2015) have conducted an impressive and tightly controlled study in which they show that women can be favored in hiring, provided that all other things are equal. …But once we introduce some of the “noise” of a real hiring situation, we can no longer be sure that the playing field is equal….
Stellar women do indeed rise to the top of candidate pools, but they must be outliers to do so. [Further] the gap between ratings of stellar and strong female candidates is often greater than the ratings gap between stellar and strong men. As a result, in a real hiring process, strong women can still end up ranked below their equally qualified “…strong” male peers.
They conclude that although the Williams and Ceci’s results are hopeful, it is “not time to throw out those training materials yet!”