Abstract Machine translation (MT) technology has facilitated our daily tasks by providing accessible shortcuts for gathering, processing, and communicating information. However, it can suffer from biases that harm users society at large. As a relatively new field of inquiry, studies gender bias in MT still lack cohesion. This advocates unified framework to ease future research. To this end, we:...

I study the impact of online instruction on teaching evaluations at a higher education institution in Spain. Using difference-in-differences approach, show that semester when moved online, female lecturers were evaluated more poorly than previous semesters. The performance male was not impacted by new environment, according to student opinion. rule out several mechanisms: for example, poorer ad...

In this work, we analyze the gender bias induced by BERT in downstream tasks. We also propose solutions to reduce bias. Contextual language models (CLMs) have pushed NLP benchmarks a new height. It has become norm utilize CLM-provided word embeddings tasks such as text classification. However, unless addressed, CLMs are prone learn intrinsic dataset. As result, predictions of can vary noticeabl...

OBJECTIVE To assess non-participation bias in a survey of male sexual behavior. MATERIAL AND METHODS A household survey was carried out in 1992-1993 using a probability sampling frame in Mexico City. Demographic variables were available for all eligible men. The extent of non-participation bias was estimated using a version of the Heckman method, which utilizes two equations, one to predict p...

Research on visual attention triggered by face gender is still relatively sparse. In the present study, three experiments are reported in which male and female participants were required to estimate the midpoint of a line (i.e., the "line bisection task"): at each end of the line a face was presented. Depending on the experimental condition, faces could be of the same gender (i.e., two males or...