Related papers: The Resume Paradox: Greater Language Differences, …
In 2016, the majority of full-time employed women in the U.S. earned significantly less than comparable men. The extent to which women were affected by gender inequality in earnings, however, depended greatly on socio-economic…
Equal pay is an essential component of gender equality, one of the Sustainable Development Goals of the United Nations. Using resume data of over ten million Chinese online job seekers in 2015, we study the current gender pay gap in China.…
I study the effects of US salary history bans which restrict employers from inquiring about job applicants' pay history during the hiring process, but allow candidates to voluntarily share information. Using a difference-in-differences…
The goal of this work is to help mitigate the already existing gender wage gap by supplying unbiased job recommendations based on resumes from job seekers. We employ a generative adversarial network to remove gender bias from word2vec…
Using a survey on wage expectations among students at two Swiss institutions of higher education, we examine the wage expectations of our respondents along two main lines. First, we investigate the rationality of wage expectations by…
This study analyzes the gender gap in desired wages using large administrative data of public job referrals, which allows us to look at the desired salaries of individuals from a wider wage distribution. We conduct a decomposition analysis…
This study examines gender disparities in communication research through citation metrics, authorship patterns, team composition, and faculty salaries. Using data from 62,359 papers across 121 communication journals, we find that while…
Large Language Models (LLMs) offer the potential to automate hiring by matching job descriptions with candidate resumes, streamlining recruitment processes, and reducing operational costs. However, biases inherent in these models may lead…
Occupational segregation is widely considered as one major reason leading to the gender discrimination in labor market. Using large-scale Chinese resume data of online job seekers, we uncover an interesting phenomenon that occupations with…
Large language models (LLMs) are increasingly being introduced in workplace settings, with the goals of improving efficiency and fairness. However, concerns have arisen regarding these models' potential to reflect or exacerbate social…
Gender discrimination in hiring is a pertinent and persistent bias in society, and a common motivating example for exploring bias in NLP. However, the manifestation of gendered language in application materials has received limited…
Workers who earn at or below the minimum wage in the United States are mostly either less educated, young, or female. Little is known, however, concerning the extent to which the minimum wage influences wage differentials among workers with…
The growing prominence of large language models (LLMs) in daily life has heightened concerns that LLMs exhibit many of the same gender-related biases as their creators. In the context of hiring decisions, we quantify the degree to which…
Gender imbalances in work environments have been a long-standing concern. Identifying the existence of such imbalances is key to designing policies to help overcome them. In this work, we study gender trends in employment across various…
Prior work shows that men and women speak with different levels of confidence, though it's often assumed that these differences are innate or are learned in early childhood. Using academic publishing as a setting, we find that language…
This study examines the behavior of Large Language Models (LLMs) when evaluating professional candidates based on their resumes or curricula vitae (CVs). In an experiment involving 22 leading LLMs, each model was systematically given one…
We take a long term look at initial employment trends for new doctorates with an eye towards gender, citizenship, and gender and citizenship differences by analyzing data from 1991-2015 AMS-ASA-IMS-MAA- SIAM Annual Surveys. The data show…
The use of Large Language Models (LLMs) in hiring has led to legislative actions to protect vulnerable demographic groups. This paper presents a novel framework for benchmarking hierarchical gender hiring bias in Large Language Models…
Current automatic speech recognition (ASR) models are designed to be used across many languages and tasks without substantial changes. However, this broad language coverage hides performance gaps within languages, for example, across…
This paper resolves the empirical puzzle in the public-private wage literature: why studies using similar data reach contradictory conclusions about wage premiums and penalties. Utilizing rich French administrative panel data (2012-2019),…