相关论文: Gender differences in grant peer review: A meta-an…

This review article provides an overview of research on the topic of gender equity in educational physics labs. As many institutions and instructors seek to evolve or transform physics lab learning, it is important that changes are made…

In this article, we draw on previous reports from physics, science education, and women's studies to propose a more nuanced treatment of gender in physics education research (PER). A growing body of PER examines gender differences in…

Sex and gender-based healthcare disparities contribute to differences in health outcomes. We focus on time to diagnosis (TTD) by conducting two large-scale, complementary analyses among men and women across 29 phenotypes and 195K patients.…

This work investigates the effect of gender-stereotypical biases in the content of retrieved results on the relevance judgement of users/annotators. In particular, since relevance in information retrieval (IR) is a multi-dimensional…

Addressing female underrepresentation in leadership positions has become a key policy objective. However, little is known about the extent to which leadership appeals differently to women. Collecting new data from a large firm, I document…

Security decisions are made by human analysts under uncertain conditions which leaves room for bias judgement. However, little is known about how demographics like gender and education impact these judgments. We conducted an empirical study…

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,…

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/ing guides how we view ourselves, the world around us, and each other--including non-humans. Critical voices have raised the alarm about stereotyped gendering in the design of socially embodied artificial agents like voice…

Reproducing concurrency bugs is a complex task due to their unpredictable behavior. Researchers, regardless of gender, are contributing to automating this complex task to aid software developers. While some studies have investigated gender…

Different methods have been proposed to develop meta-embeddings from a given set of source embeddings. However, the source embeddings can contain unfair gender-related biases, and how these influence the meta-embeddings has not been studied…

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…

The rise of concern around Natural Language Processing (NLP) technologies containing and perpetuating social biases has led to a rich and rapidly growing area of research. Gender bias is one of the central biases being analyzed, but to date…

Although different organizations have defined policies towards diversity in academia, many argue that minorities are still disadvantaged in university admissions due to biases. Extensive research has been conducted on detecting partiality…

Peer review in grant evaluation informs funding decisions, but the contents of peer review reports are rarely analyzed. In this work, we develop a thoroughly tested pipeline to analyze the texts of grant peer review reports using methods…

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…

Bias-measuring datasets play a critical role in detecting biased behavior of language models and in evaluating progress of bias mitigation methods. In this work, we focus on evaluating gender bias through coreference resolution, where…

Gender bias in machine translation (MT) is recognized as an issue that can harm people and society. And yet, advancements in the field rarely involve people, the final MT users, or inform how they might be impacted by biased technologies.…

Research on acknowledgment sections of scientific papers has gained significant attention, but there remains a dearth of studies examining acknowledgments in the context of Electronic Theses and Dissertations. This paper addresses this gap…

Large language models (LLMs) acquire beliefs about gender from training data and can therefore generate text with stereotypical gender attitudes. Prior studies have demonstrated model generations favor one gender or exhibit stereotypes…