Markus Eberhardt, Giovanni Facchini, Valeria Rueda, 08 February 2022

Academia faces increased scrutiny because of its gender imbalance. This column uses machine learning methods to analyse gendered patterns in the text of reference letters written for candidates for entry-level positions in the economics job market. The findings reveal that women are systematically more likely to be praised for being hardworking and at times less likely to be praised for their ability. Given the time and effort letter writers devote to supporting their students, the authors suggest this gender stereotype is likely due to unconscious biases.

Eliana La Ferrara, 11 October 2019

Eliana la Ferrara discusses her research on how to leverage the positive effects of racial diversity.

Elena Cettolin, Sigrid Suetens, 13 September 2017

Studies have shown that ethnic discrimination occurs in many countries across Europe and the rest of the world, but distinguishing between discrimination based on ‘stereotypes’ and on ‘tastes’ is difficult. This column presents results from an experiment in the Netherlands that isolated taste-based discrimination. The results suggest that native Dutch participants reciprocate trust placed in them by immigrants of non-Western less than they reciprocate the trust of fellow Dutch natives. Since trustworthiness involves no behavioural risk, this implies that discrimination is the consequence of not only stereotyping, but also of tastes.

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