The QMC would like to thank everyone who was able to attend our Fall 2021 Speaker Series, which tackled a variety of issues related to quantitative data! Information on the talks, including video recordings and additional material, can be found below.
Please look out for updates about our upcoming Spring 2022 Speaker Series on our website and our News from the QMC! As a brief reminder, all presentations for the 2021 – 2022 academic year will be held virtually via Zoom, and registration will be required for attendees to receive a Zoom link.
Please direct any further questions to our QMC email, qmc@osu.edu, or to our Associate Director Brian Timm (timm.21).
Fall Semester 2021 Speakers
Wednesday, September 8th, 3:30 – 4:30 pm: Dr. Manuel Eisner, University of Cambridge, UK
Title: The Pitfalls of Data Portals: A look at Cross-National Homicide Rates
Dr. Manuel Eisner (he/him/his) is the Director of the Violence Research Centre and Wolfson Professor of Criminology at the University of Cambridge, UK. Dr. Eisner has published several books, book chapters, and over 100 journal articles on the causes and consequences of interpersonal violence across human societies. Dr. Eisner’s recent work was featured in Psychological Science, entitled “The Pitfalls of Using Data Portals as Sources for Psychological Research: The Example of Cross-National Homicide Data.” The article describes issues researchers can consider when using data from open-access data portals (e.g., World Health Organization, UNICEF) or when reading articles that contain these data.
Registration for Dr. Eisner’s talk is now closed.
Click the link below to access “The Pitfalls of Using Data Portals as Sources for Psychological Research: The Example of Cross-National Homicide Data.”
2021_Eisner_The Pitfalls of Using Data Portals as Sources for Psychological Research
Wednesday, October 6th, 3:30 – 4:30 pm: Dr. Elizabeth Tipton, Northwestern University
Title: Using Generalization to Improve the Accuracy of Education Studies
Dr. Elizabeth Tipton (she/her/hers) is an Associate Professor of Statistics at Northwestern University and Co-Director of the Statistics for Evidence-Based Policy and Practice Center. She has published numerous articles in peer-reviewed journals, including the Journal of Educational and Behavioral Statistics, Statistics in Medicine, Psychological Methods, and the Journal of Research on Educational Effectiveness. Her work has received support from the National Science Foundation, the Institute for Education Sciences, and the Spencer Foundation.
Dr. Tipton’s research focuses on the design and analysis of field experiments. She has designed methods and tools to improve the generalizability of randomized control trials, especially in education and psychology. In her presentation, Dr. Tipton will provide concrete steps researchers should take when designing studies so that the studies produce generalizable results.
Registration for this event has been closed. The full video for this presentation can be found here. You can also access Dr. Tipton’s PowerPoint slides from her presentation here.
To learn more about Dr. Tipton and her research visit https://www.bethtipton.com/.
Below are some noteworthy readings from Professor Tipton.
Tipton, E. & Matlen, B. (2019) Improved generalizability through improved recruitment: Lessons learned from a large-scale randomized trial. American Journal of Evaluation, 40(3), 414–430. https://doi.org/10.1177/1098214018810519
Tipton, E. & Olsen, R. B. (2018). A review of statistical methods for generalizing from evaluations of educational interventions. Educational Researcher, 47(8), 516-524. https://doi.org/10.3102/0013189X18781522
Wednesday, November 3rd, 3:30 – 4:30 pm: Dr. Alex Hanna, Google
Title: Beyond Bias: Algorithmic Unfairness, Infrastructure, and Genealogies of Data
Dr. Alex Hanna (she/her/hers) is a sociologist and senior research scientist on the Ethical AI team at Google. Her research centers on origins of training data which form the informational infrastructure of machine learning, artificial intelligence, and algorithmic fairness frameworks. In addition, her research focuses on student social movements and university responses in the United States and Canada. She has taught a variety of workshops and courses on computational sciences. Dr. Hanna has co-authored articles for publications including Mobilization, The ANNALS of the American Academy of Political and Social Science, American Behavioral Scientist, and Big Data & Society. Dr. Hanna received her PhD in Sociology in 2016 from the University of Wisconsin-Madison.
Registration for Dr. Hanna’s talk has now closed. The full video from Dr. Hanna’s talk can be found here.