Decoy Effects Improve Diversity Hiring

A growing literature demonstrates that when making choices among multiple options, decision makers are strongly influenced by the mere presence of additional options, even when those options are largely undesirable and are never actually selected. The effects of irrelevant options on decisions, often called decoy effects, have been observed in hiring and admissions decisions where the nature of a third candidate can radically shift preferences. In this study, we examine the influence of decoy effects on diversity hiring and extend research by examining choices with more than two organizational goals. Results indicate that the presence of a second candidate who meets diversity goals markedly increases how frequently decision makers indicate that they would make an offer to diverse candidates. This effect occurs even when decision makers must sacrifice some credential quality to obtain the diverse candidate. Overall, diverse candidates are more likely to receive offers when more than one diversity candidate is included in the finalist pool. The practical implications are clear: When a major organizational goal is to increase diversity, a policy that includes evaluating multiple diverse candidates in a final applicant slate should be considered

Additional Laparotomy Sponges Requested During Cesarean Delivery: \u27Early Warning\u27 Associated with Postpartum Hemorrhage

https://digitalcommons.unmc.edu/emet_posters/1015/thumbnail.jp

The Prosocial and Aggressive Driving Inventory (PADI): A Self-Report Measure of Safe and Unsafe Driving Behaviors

Surveys of 1217 undergraduate students supported the reliability (inter-item and test-retest) and validity of the Prosocial and Aggressive Driving Inventory (PADI). Principal component analyses on the PADI items yielded two scales: Prosocial Driving (17 items) and Aggressive Driving (12 items). Prosocial Driving was associated with fewer reported traffic accidents and violations, with participants who were older and female, and with lower Boredom Susceptibility and Hostility scores, and higher scores on Agreeableness, Conscientiousness, Openness, and Neuroticism. Aggressive Driving was associated with more frequent traffic violations, with female participants, and with higher scores on Competitiveness, Sensation Seeking, Hostility, and Extraversion, and lower scores on Conscientiousness, Agreeableness, and Openness. The theoretical and practical implications of the PADI’s dual focus on safe and unsafe driving are discussed

Overview of the MOSAiC expedition - Atmosphere

With the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore cross-cutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge. The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic

\u3cem\u3epsychmeta\u3c/em\u3e: An R Package for Psychometric Meta-Analysis

Over the past four decades, psychometric meta-analysis (PMA) has emerged a key way that psychological disciplines build cumulative scientific knowledge. Despite the importance and popularity of PMA, software implementing the method has tended to be closed-source, inflexible, limited in terms of the psychometric corrections available, cumbersome to use for complex analyses, and/or costly. To overcome these limitations, we created the psychmeta R package: a free, open-source, comprehensive program for PMA

Not Restricted to Selection Research: Accounting for Indirect Range Restriction in Organizational Research

Range restriction is a common problem in organizational research and is an important statistical artifact to correct for in meta-analysis. Historically, researchers have had to rely on range-restriction corrections that only make use of range-restriction information for one variable, but it is not uncommon for researchers to have such information for both variables in a correlation (e.g., when studying the correlation between two predictor variables). Existing meta-analytic methods incorporating bivariate range-restriction corrections overlook their unique implications for estimating the sampling variance of corrected correlations and for accurately assigning weights to studies in individual-correction meta-analyses. We introduce new methods for computing individual-correction and artifact-distribution meta-analyses using the bivariate indirect range restriction (BVIRR; “Case V”) correction and describe improved methods for applying BVIRR corrections that substantially reduce bias in parameter estimation. We illustrate the effectiveness of these methods in a large-scale simulation and in meta-analyses of expatriate data. We provide R code to implement the methods described in this article; more comprehensive and robust functions for applying these methods are available in the psychmeta package for R

The Prosocial and Aggressive Driving Inventory (PADI): A Self-Report Measure of Safe and Unsafe Driving Behaviors

Surveys of 1217 undergraduate students supported the reliability (inter-item and test–retest) and validity of the Prosocial and Aggressive Driving Inventory (PADI). Principal component analyses on the PADI items yielded two scales: Prosocial Driving (17 items) and Aggressive Driving (12 items). Prosocial Driving was associated with fewer reported traffic accidents and violations, with participants who were older and female, and with lower Boredom Susceptibility and Hostility scores, and higher scores on Agreeableness, Conscientiousness, Openness, and Neuroticism. Aggressive Driving was associated with more frequent traffic violations, with female participants, and with higher scores on Competitiveness, Sensation Seeking, Hostility, and Extraversion, and lower scores on Conscientiousness, Agreeableness, and Openness. The theoretical and practical implications of the PADI\u27s dual focus on safe and unsafe driving are discussed