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Large Language Models (LLMs) have made substantial progress in the past several months, shattering state-of-the-art benchmarks in many domains. This paper investigates LLMs' behavior with respect to gender stereotypes, a known issue for…
A person's gender is a crucial piece of information when performing research across a wide range of scientific disciplines, such as medicine, sociology, political science, and economics, to name a few. However, in increasing instances,…
As social issues related to gender bias attract closer scrutiny, accurate tools to determine the gender profile of large groups become essential. When explicit data is unavailable, gender is often inferred from names. Current methods follow…
Algorithmic discrimination is an important aspect when data is used for predictive purposes. This paper analyzes the relationships between discrimination and classification, data set partitioning, and decision models, as well as…
Several studies of the Job Corps tend to nd more positive earnings effects for males than for females. This effect heterogeneity favouring males contrasts with the results of the majority of other training programmes' evaluations. Applying…
Most existing notions of algorithmic fairness are one-shot: they ensure some form of allocative equality at the time of decision making, but do not account for the adverse impact of the algorithmic decisions today on the long-term welfare…
Societal bias towards certain communities is a big problem that affects a lot of machine learning systems. This work aims at addressing the racial bias present in many modern gender recognition systems. We learn race invariant…
Urban vibrancy is the dynamic activity of humans in urban locations. It can vary with urban features and the opportunities for human interactions, but it might also differ according to the underlying social conditions of city inhabitants…
We propose a set of conservative models in which agents exchange wealth with a preference in the choice of interacting agents in different ways. The common feature in all the models is that the temporary values of financial status of agents…
This paper examines the impact of racial discrimination in hiring on employment, wages, and wealth disparities between black and white workers. Using a labor search-and-matching model with racially prejudiced and non-prejudiced firms, we…
Gender norms are widely recognized as key determinants of persistent gender gaps in the labor market. However, our understanding of the drivers of gender norms, and their implications for preferences, remain lacking. This paper addresses…
Gender differences in human behaviour have attracted generations of social scientists, who have explored whether males and females act differently in domains involving competition, risk taking, cooperation, altruism, honesty, as well as…
With widening deployments of natural language processing (NLP) in daily life, inherited social biases from NLP models have become more severe and problematic. Previous studies have shown that word embeddings trained on human-generated…
Gender bias represents a form of systematic negative treatment that targets individuals based on their gender. This discrimination can range from subtle sexist remarks and gendered stereotypes to outright hate speech. Prior research has…
Women have become better represented in business, academia, and government over time, yet a dearth of women at the highest levels of leadership remains. Sociologists have attributed the leaky progression of women through professional…
How much meaning influences gender assignment across languages is an active area of research in linguistics and cognitive science. We can view current approaches as aiming to determine where gender assignment falls on a spectrum, from being…
Recent studies show that gender diversity in IT teams has a positive impact on the software development process. However, there is still a great gender inequality. The aim of our study was to examine how the working atmosphere depends on…
Gender bias in artificial intelligence has become an important issue, particularly in the context of language models used in communication-oriented applications. This study examines the extent to which Large Language Models (LLMs) exhibit…
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),…
This paper presents quasi-experimental research examining the effect of both local and state anti-discrimination laws on sexual orientation on the labor supply and wages of lesbian, gay, and bisexual (LGB) workers. To do so, we use the…