Dr. Brittany Perry, Instructional Associate Professor, Texas A&M University at College Station
Although the representation of women and minorities in STEM subjects has improved in recent decades, a lack of diversity remains an issue across a range of fields (e.g. Porter and Serra, 2019; APLU, 2016). Within political science, gender and race gaps are especially pronounced in mathematically-oriented subfields, including quantitative methodology and formal theory. As an example, whereas women constitute 37% of members of the American Political Science Association (APSA), only 24.25% of members in the methodology section are women. Latinos make up only 6% of APSA memberships and Black individuals only account for 4.86%. In political methodology, only 1.7% of APSA members are Black/African American (APSA, 2019).
This trend can partly be traced back to political science education, both at the undergraduate and graduate level. At the graduate level, the underrepresentation of racial and ethnic minorities has drawn renewed public critique. Chris Roudiez, a UMD economics graduate student, recently complied data from The National Center for Education Statistics showing a dearth of racial and ethnic diversity among graduates in the top political science Ph.D. programs.
So how do we close the diversity gap in Ph.D. graduates and specifically in the political methodology subfield? One avenue is to make quantitative social science more accessible to underrepresented students. In evaluating the gender gap in STEM fields, scholars have shown that encouragement and information sharing on the benefits of acquired skills can boost women’s interest and enrollment (Bayer and Rouse, 2016; Barnes, 2018). We also know that providing research opportunities increases retention of students of color and increases the likelihood they will pursue advanced STEM degrees (e.g. Gregerman et al, 1998; Russell et al, 2007).
Drawing from this research, and the thoughtful brainstorming and model programming across political science (e.g. the Ralph Bunche Program at Duke University and the Emerging Scholars Program at The University of Michigan), the Department of Political Science at Texas A&M University has developed The Data Lab @TAMUPOLS. In the two-day workshop, undergraduate or master’s students gain hands-on experience managing, visualizing, analyzing, and interpreting data in Stata software. Under the guidance of a professional instructor (who has donated time from StataCorp) and graduate student assistants, participating students work through sample datasets, solve practice problems, and develop skills to apply to their own research and future pursuits.
Students are also exposed to current academic research and research careers via keynote research talks by TAMU faculty. They meet with other TAMU political science faculty, spend time with TAMU Ph.D. students, and speak with the Political Science graduate director about our program, as well as the application process.
Key to the continued success of the program is recruitment and sustained communication with participant students after the Lab. We began months in advance to recruit across Texas A&M and at surrounding institutions. In our inaugural year, I personally contacted department heads and faculty at other Texas colleges and universities to help encourage top candidates to apply. We also partnered with The Minority Graduate Placement Program (MIGAP) to fund travel and accommodations for seven Data Lab participants from The University of Puerto Rico.
Nearly all students came into the Data Lab with limited knowledge of data science and coding, but most left with concrete skills and enthusiasm for continuing data science education. 68% of students said that their knowledge of programming “improved a great deal/ a lot” and there was a marked increase in the number of students who strongly agreed with the statement: It is important for people like me to learn quantitative methods (from 48% strongly agreeing with this statement prior to the lab to 63% strongly agreeing after the lab experience).
In our efforts to continue supporting participants, we provided certificates of completion and formal recommendation letters upon request. I also continue to share additional research opportunities via email. In line with the mentoring literature, we hope that building longer-term relationships with students will increase our programmatic effectiveness (Grossman and Rhodes, 2002).
Although the COVID-19 pandemic means the Data Lab will be hosted virtually this coming year, we plan to recreate our inaugural experience as much as possible. With the virtual format and no travel costs, we are also able to cast a wider net and accept more students from outside of the state. Currently, we are working with Stata to find creative ways to connect with students at home. We will provide temporary Stata licenses to all participants and offer one-on-one graduate support throughout the lab. In addition, we will have breakout room activities and provide “A&M care packages” via mail so students can continue to have an opportunity to network with each other and feel apart of the TAMU community.
We are now accepting applications to the Data Lab @TAMUPOLS for January 11-12, 2020. Please follow the hyperlink to the application or contact Dr. Brittany Perry at email@example.com. Applications are due November 13, 2020.
Association of Public and Land Grant Universities (APLU). 2016. “Increasing Diversity in the Biomedical Research Workforce.” https://www.aplu.org/library/increasing-diversity-in-the biomedical-research-workforce.
Barnes, T.D. (2018). Strategies for Improving Gender Diversity in the Methods Community:
Insights from Political Methodologists and Social Science Research.PS: Political Science and Politics, 51(3), 580-587.
Bayer, A. and Rouse, C.E. (2016). Diversity in the economics profession: A new
attack on an old problem. The Journal of Economic Perspectives, 30(4), 221–242.
Gregerman, S. R., Lerner, J. S., Von Hippel, W., Jonides, J., & Nagda, B. A. (1998). Undergraduate student-faculty research partnerships affect student retention. The Review of Higher Education, 22(1), 55-72.
Grossman, J. B., & Rhodes, J. E. (2002). The test of time: Predictors and effects of duration in youth mentoring programs. American Journal of Community Psychology, 30, 199–206.
Porter, C., & Serra, D. (2019). Gender differences in the choice of major: The importance of female role models. American Economic Journal: Applied Economics.