Comparative analysis of automatic gender detection from names: evaluating the stability and performance of ChatGPT <i>versus</i> Namsor, and Gender-API.

ABSTRACT: The gender classification from names is crucial for uncovering a myriad of gender-related research questions. Traditionally, this has been automatically computed by gender detection tools (GDTs), which now face new industry players in the form of conversational bots like ChatGPT. This paper statistically tests the stability and performance of ChatGPT 3.5 Turbo and ChatGPT 4o for gender detection. It also compares two of the most used GDTs (Namsor and Gender-API) with ChatGPT using a dataset of 5,779 records compiled from previous studies for the most challenging variant, which is the gender inference from full name without providing any additional information. Results statistically show that ChatGPT is very stable presenting low standard deviation and tight confidence intervals for the sam

SUBMITTER: Dominguez-Diaz A 

PROVIDER: S-EPMC11623165 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature