Related Experiment Video
Updated: Oct 27, 2025

A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences
Published on: September 4, 2019
A quasi-experimental study of ethnic and gender bias in university grading
Carina Saxlund Bischoff1, Anders Ejrnæs1, Olivier Rubin1
1Department of Social Sciences and Business, Roskilde University, Roskilde, Denmark.
Abstract:
This paper contributes to the debate on race- and gender-based discrimination in grading. We apply a quasi-experimental research design exploiting a shift from open grading in 2018 (examinee's name clearly visible on written assignments), to blind grading in 2019 (only student ID number visible). The analysis thus informs name-based stereotyping and discrimination, where student ethnicity and gender are derived from their names on written assignments. The case is a quantitative methods exam at Roskilde University (Denmark). We rely on OLS regression models with interaction terms to analyze whether blind grading has any impact on the relative grading differences between the sexes (female vs. male examinees) and/or between the two core ethnic groups (ethnic minorities vs. ethnic majority examinees). The results show no evidence of gender or ethnic bias based on names in the grading process. The results were validated by several checks for robustness. We argue that the weaker evidence of ethnic discrimination in grading vis-à-vis discrimination in employment and housing suggests the relevance of gauging the stakes involved in potentially discriminatory activities.
More Related Videos
07:32Use of Galvanic Skin Responses, Salivary Biomarkers, and Self-reports to Assess Undergraduate Student Performance During a Laboratory Exam Activity
Published on: February 10, 2016
09:03Post-Movie Subliminal Measurement PMSM, for Investigating Implicit Social Bias
Published on: February 29, 2020
Related Concept Videos
Stereotypes, Prejudice, and Discrimination
Bias
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
Surveys
Stereotype Threat and Self-fulfilling Prophecies
Confirmation Biases
Group Design