Gender, Socioeconomic Class, and Interview Invites

Description

Resumes were sent out to 316 top law firms in the United States, and there were two randomized characteristics of each resume. First, the gender associated with the resume was randomized by assigning a first name of either James or Julia. Second, the socioeconomic class of the candidate was randomly assigned and represented through five minor changes associated with personal interests and other other minor details (e.g. an extracurricular activity of sailing team vs track and field). The outcome variable was whether the candidate was received an interview.

Usage

law_resume

Format

A data frame with 316 observations on the following 3 variables. Each row represents a resume sent a top law firm for this experiment.

class

The resume represented irrelevant details suggesting either "low" or "high" socioeconomic class.

gender

The resume implied the candidate was either "male" or "female".

outcome

If the candidate received an invitation for an "interview" or "not".

Source

For a casual overview, see https://hbr.org/2016/12/research-how-subtle-class-cues-can-backfire-on-your-resume.

For the academic paper, see Tilcsik A, Rivera LA. 2016. Class Advantage, Commitment Penalty. The Gendered Effect of Social Class Signals in an Elite Labor Market. American Sociological Review 81:6 p1097-1131. doi:10.1177/0003122416668154.

Examples

tapply(law_resume$outcome == "interview", law_resume[, c("class", "gender")], mean)
m <- glm(I(outcome == "interview") ~ gender * class, data = law_resume, family = binomial)
summary(m)
predict(m, type = "response")