Faculty Talk: Misha Teplitskiy

Wed, 01/16/2019 - 12:00pm to 1:00pm

Ehrlicher Room, 3100 North Quad

How Status and Culture Shape the Creation and Evaluation of New Ideas


This talk will focus on the roles that status and culture play in how people create and evaluate new ideas. I will first describe my recent work on how political divisions affect collaboration on Wikipedia and the quality of the pages editors create. I will then describe how professional networks affect peer evaluation of scientific research articles. The majority of the presentation will focus on a field experiment that investigates the pathways through which culture “intervenes” in expert evaluation. This experiment asks, “When experts disagree, whose opinion counts?” To answer this question, my co-authors and I collaborated with Harvard Medical School to run a randomized controlled trial in the review of real grant proposals. After receiving independent reviews from 277 faculty members, we exposed the reviewers to artificial scores attributed to anonymous “other reviewers,” and enabled them to change their initial scores. We found that women changed their scores substantially more often than men, particularly when they were underrepresented in their subfield. Meanwhile, very high-status reviewers changed their scores 24% less often than others. These findings show that disparities in influence on group decisions can arise even without any discrimination from others, because experts self-discount their expertise in line with cultural stereotypes. Self-discounting helps explain why altering the composition of decision-making groups, without altering their decision process, may have no effect on outcomes. I will conclude by showing new evidence that high (low) citations to academic works cause them to be perceived as being of higher (lower) quality.  

Speaker Bio

Misha Teplitskiy is a Postdoctoral Fellow at the Laboratory for Innovation Science at Harvard University. He received his PhD in Sociology from the University of Chicago. His research applies computational and experimental techniques to understand the roles that status and culture play in the production of knowledge.