Human annotated data plays a crucial role in machine learning (ML) research and
development. However, the ethical considerations around the processes and decisions that …

Social stereotypes negatively impact individuals' judgments about different groups and may
have a critical role in understanding language directed toward marginalized groups. Here …

Machine learning models are commonly used to detect toxicity in online conversations.
These models are trained on datasets annotated by human raters. We explore how raters' …

Human feedback is central to the alignment of Large Language Models (LLMs). However,
open questions remain about the methods (how), domains (where), people (who) and …

Moderation is crucial to promoting healthy on-line discussions. Although severaltoxicity'
detection datasets and models have been published, most of them ignore the context of the …

Music is present in every known society but varies from place to place. What, if anything, is
universal to music cognition? We measured a signature of mental representations of rhythm …

Microaggressions are subtle, often veiled, manifestations of human biases. These uncivil
interactions can have a powerful negative impact on people by marginalizing minorities and …

Human annotations play a crucial role in machine learning (ML) research and development.
However, the ethical considerations around the processes and decisions that go into …

This chapter provides an overview of convenience sampling in political science
experimental research. We first define convenience sampling and track its use in political …

When computers unexpectedly delay or thwart goal attainment, frustration ensues. The
central studies of the extent, content, and impact of such frustration were done more than 15 …