Tag: Data

In this section we analyze the LOR features across our study groups. We first compare the LORs by applicant gender and identify statistically significant features among the variables outlined in Table 1. We are also interested in learning if any observed applicant biases are present among the male and female recommenders. We next conduct a parallel study where we swap the roles of recommender and applicant gender and compare the LORs by recommender gender and examine these differences while controlling the applicant gender. Lastly, we present the findings across three culture groups (i.e., US, China, and India).

Comparing LORs by applicant gender while controlling for recommender gender

Table 3 summarizes the differences between LORs written for female and male applicants, with further analysis on the recommender’s gender. The results only include features for which the differences by applicant gender are statistically significant with a 95% confidence.

Without considering recommender gender,