Anonymized Resume Data Supporting the Study of the Gender Pay Gap in China: Insights from a Discrimination Perspective

This dataset provides a fully anonymized and structured sample that supports the main empirical findings of the associated study on gender pay gaps in online labor markets. The data consist of 753,616 individual resume records collected from multiple online recruitment platforms in 2015 through officially provided open APIs. To ensure privacy protection and ethical compliance, all direct personal identifiers have been removed, and sensitive information has been anonymized. The dataset includes key demographic and human capital variables commonly used in labor market research, including gender, age, work tenure, educational degree, university type, last annual salary, marital status, major, industry, position, city of birth, current city, and the city where the job is sought. Except for the last annual salary and categorical variables, all continuous variables are Z-standardized. The dataset is designed to preserve the statistical structure necessary to replicate the main analytical procedures, including Blinder–Oaxaca decomposition analyses, while preventing the identification of individuals. Due to privacy, ethical, and contractual restrictions associated with the original resume data, the full raw dataset cannot be made publicly available. This released dataset serves as an anonymized analytical sample intended for research transparency and reproducibility. Researchers interested in accessing the original data may contact the corresponding author, subject to institutional and ethical approval.