Related papers: The Resume Paradox: Greater Language Differences, …
We measure human capital using the self-reported skill sets of nearly 9 million U.S. college graduates from professional profiles on LinkedIn. We aggregate skill strings into 48 clusters of general, occupation-specific, and managerial…
We conducted a large-scale resume audit of 36,880 applications to 9,220 job advertisements for new college graduates across the United States. Firms express task preferences through job-advertisement text, which we link to occupation-level…
An ever-widening workforce gap exists in the global cybersecurity industry but diverse talent is underutilized. The global cybersecurity workforce is only 25% female. Much research exists on the effect of gender bias on the hiring of women…
It is well known that women are underrepresented in the academic systems of many countries. Gender discrimination is one of the factors that could contribute to this phenomenon. This study considers a recent national academic recruitment…
In this paper, I introduce a novel decomposition method based on Gaussian mixtures and k-Means clustering, applied to a large Brazilian administrative dataset, to analyze the gender wage gap through the lens of worker-firm interactions…
Although the gender gap in academia has narrowed, females are underrepresented within some fields in the USA. Prior research suggests that the imbalances between science, technology, engineering and mathematics fields may be partly due to…
Efforts to combat continuing gender inequalities in academia need to be informed by evidence about where differences occur. Citations are relevant as potential evidence in appointment and promotion decisions, but it is unclear whether there…
Surveys are an indispensable source of data for applied economic research; however, their reliance on self-reported information can introduce bias, especially if core variables such as personal income are misreported. To assess the extent…
Although approximately 50% of medical school graduates today are women, female physicians tend to be underrepresented in senior positions, make less money than their male counterparts and receive fewer promotions. There is a growing body of…
This paper aims to evaluate how changing patterns of sectoral gender segregation play a role in accounting for women's employment contracts and wages in the UK between 2005 and 2020. We then study wage differentials in gender-specific…
Current attempts to address the shortfall of female researchers in Science, Technology, Engineering and Mathematics (STEM) have not yet succeeded despite other academic subjects having female majorities. This article investigates the extent…
The purpose of this study is to find evidence for supporting the hypothesis that language is the mirror of our thinking, our prejudices and cultural stereotypes. In this analysis, a questionnaire was administered to 537 people. The answers…
Although systematic biases in decision-making are widely documented, the ways in which they emerge from different sources is less understood. We present a controlled experimental platform to study gender bias in hiring by decoupling the…
Large Language Models (LLMs) are finding applications in all aspects of life, but their susceptibility to biases, particularly gender stereotyping, raises ethical concerns. This study introduces a novel methodology, a persona-based…
Self-promotion in science is ubiquitous but may not be exercised equally by men and women. Research on self-promotion in other domains suggests that, due to bias in self-assessment and adverse reactions to non-gender-conforming behaviors…
This research delves into the reduction of machine learning model bias through Ensemble Learning. Our rigorous methodology comprehensively assesses bias across various categorical variables, ultimately revealing a pronounced gender…
This study investigates gender bias in large language models (LLMs) by comparing their gender perception to that of human respondents, U.S. Bureau of Labor Statistics data, and a 50% no-bias benchmark. We created a new evaluation set using…
We analyze and develop a quantitative model describing the evolution of personal income distribution, PID, for males and females in the U.S. between 1930 and 2014. The overall microeconomic model, which we introduced ten years ago,…
Gender biases in language generation systems are challenging to mitigate. One possible source for these biases is gender representation disparities in the training and evaluation data. Despite recent progress in documenting this problem and…
The extent to which men and women use language differently has been questioned previously. Finding clear and consistent gender differences in language is not conclusive in general, and the research is heavily influenced by the context and…