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The proliferation of personalized recommendation technologies has raised concerns about discrepancies in their recommendation performance across different genders, age groups, and racial or ethnic populations. This varying degree of…
False assumptions about sex and gender are deeply embedded in the medical system, including that they are binary, static, and concordant. Machine learning researchers must understand the nature of these assumptions in order to avoid…
It is a well-studied notion that women are under-represented in the physical sciences, with a "leaky pipeline" metaphor describing how the number of women decreases at higher levels in academia[1,2]. It is unclear, however, where the major…
The literature dedicated to analysis of the difference in research productivity between the sexes tends to agree in indicating better performance for men. This study enters in the vein of work on the subject. Through bibliometric…
It is widely acknowledged that there is a diversity problem in genomics stemming from the vast underrepresentation of non-European genetic ancestry populations. While many challenges exist to address this gap, a major complicating factor is…
Name-based gender prediction has traditionally categorized individuals as either female or male based on their names, using a binary classification system. That binary approach can be problematic in the cases of gender-neutral names that do…
Despite increasing representation in graduate training programs, a disproportionate number of women leave academic research before obtaining an independent position. To understand factors underlying this trend, we analyzed a…
Laboratory studies for planetary science and astrobiology aimat advancing our understanding of the Solar System through the promotion of theoretical and experimental research into the underlying processes that shape it. Laboratory studies…
While not all researchers prioritize social impact, it is undeniably a crucial aspect that adds significance to their work. The objective of this paper is to explore potential gender differences in the social attention paid to researchers…
Historically, physics has been a predominantly male field, with previous literature showing there is little diversity amongst U.S. physics students at the undergraduate and graduate levels. Recent research indicates that the lack of…
This study discusses factors that keep women from entering science and technology, which include social stereotypes that they struggle against, lack of maternity leave and other basic human rights, and the climate that makes them leave…
We address the critical issue of biased algorithms and unfair rankings, which have permeated various sectors, including search engines, recommendation systems, and workforce management. These biases can lead to discriminatory outcomes in a…
Algorithmic fairness has emerged as a critical concern in artificial intelligence (AI) research. However, the development of fair AI systems is not an objective process. Fairness is an inherently subjective concept, shaped by the values,…
The "gender" of intelligent agents, virtual characters, social robots, and other agentic machines has emerged as a fundamental topic in studies of people's interactions with computers. Perceptions of agent gender can help explain user…
Efforts to promote equity and inclusion using evidence-based approaches are vital to correcting long-standing societal inequities that have disadvantaged women and discouraged them from pursuing studies, including in many STEM disciplines.…
In recent years, significant advancements in the field of Natural Language Processing (NLP) have positioned commercialized language models as wide-reaching, highly useful tools. In tandem, there has been an explosion of multidisciplinary…
Employers are adopting algorithmic hiring technology throughout the recruitment pipeline. Algorithmic fairness is especially applicable in this domain due to its high stakes and structural inequalities. Unfortunately, most work in this…
We investigate inequalities in access to permanent positions in professional astronomy in France, focusing on the hiring stage. We use results from a national survey conducted on behalf of the French society of astronomy and astrophysics…
Computational social scientists often harness the Web as a "societal observatory" where data about human social behavior is collected. This data enables novel investigations of psychological, anthropological and sociological research…
Gender classification algorithms have important applications in many domains today such as demographic research, law enforcement, as well as human-computer interaction. Recent research showed that algorithms trained on biased benchmark…