Are University Admissions Academically Fair?

Abstract

Admission practices at high-profile universities are often criticized for undermining academic merit. Popular tests for detecting such biases suffer from omitted characteristic bias. We develop a bounds-based test to circumvent this problem. We assume that students who are better qualified on observables would, on average, appear academically stronger to admission officers based on unobservables. This assumption reveals the sign of differences in admission standards across demographic groups that are robust to omitted characteristics. Applying our methods to admissions data from a British university, we find higher admission standards for men and slightly higher ones for private school applicants, despite equal admission success probability across gender and school background.

Men, women and STEM: Why the differences and what should be done?

“…• At some elite universities, the academic threshold for admission is higher for men than for women. This is true, for instance, at Oxford University in the UK (Bhattacharya et al, 2017) and Harvard University in the US (Arcidiacono et al, 2019, Table D5). • STEM professors are more receptive to meeting requests from female students than male students (C. Young et al, 2019).…”

Does Implicit Bias Predict Dictator Giving?

“…7 The state of this debate was recently summarized in more detail by Singal [29]. 8 In untabulated results, I confirm demographic balance between dictator and receiver roles. This experiment differs from a standard game in that some treatments employ a sorting environment.…”

“…In a standard dictator game, subjects are randomly split into receivers and dictators upon arriving at the lab. 8 A first mover is given $10 and asked how much she/he would like to give to a paired (and passive) receiver. Her/his choice ends the game.…”

“…A notable feature of sorting designs is they allow us to identify the marginal giver [7]. Recent work in other domains (e.g., college admissions) has demonstrated that detecting bias requires comparing marginal rather than average entrants [8]. Further, people are unwilling to make judgments about individuals of different races [9].…”

Enterprises Build Sustainable Innovation Loop: Take ByteDance Launching Lark as an Example

“…For instance, think of reducing the gender gap in university admissions. Bhattacharya et al (2017) show that such gap reduction typically happens at the expense of applicants with borderline academic abilities. In terms of classification (passed/ not passed), this corresponds to the group where we are least certain in the evaluation of one's academic abilities.…”