We examine the social perception of emotional intelligence (EI) through the use of observer ratings. Individuals frequently judge others’ emotional abilities in real-world settings, yet we know little about the properties of such ratings.
Theory building from multiple cases has generated some of the most cited and intriguing research over the last 80 years. Yet there remains confusion regarding how to judge its rigor.
Research on dyadic meta-accuracy suggests that people can accurately judge how their acquaintances feel toward them. However, existing studies have focused exclusively on positive feelings, such as liking. We present the first research on dyadic meta-accuracy for competition, a common dynamic among work colleagues.
In evaluating suppliers in complex purchasing decisions involving customized solutions, purchasing managers must judge the capabilities suppliers have to provide the solutions, a judgment that often includes considerable uncertainty.
A large body of social science evidence indicates that objective, reliable and valid risk assessment instruments are more accurate in evaluating risk than professional human judgements alone. In the world of pretrial detention, where more than 10 million people are jailed each year in the United States after arrest, pretrial risk assessment tools may provide a more efficient, transparent and fairer basis for making assessments than having a judge quickly scan documents detailing the defendant’s prior record and current charges and make a decision in mere minutes. However, these assessments will retain any bias present in the data used by criminal justice agencies.
Join our panel of experts who will share their technological, legal and social expertise to answer the questions raised by the real-world performance of risk assessment instruments.
Firms continue to strive for greater representation on corporate boards. One California law, attempting to mandate such greater representation, has encountered a recent setback. Two experts discuss obstacles to more diverse corporate leadership and offer approaches for surmounting them.
Research from UNC Kenan-Flagler Finance Professor Eric Ghysels attaches explicit costs to a model’s classification errors, in this case concerning pretrial detention decisions, avoiding the one-size-fits-all symmetrical cost function of traditional machine learning.
In recent months, mechanisms that have allowed for high-skilled foreign nationals to study and work in the U.S. have been put on the policy chopping block. In this Kenan Insight, we discuss why high-skilled foreign workers are critical to America's economic health, and why policies must continue to support their entry into the U.S.