A review of perceived diversity in teams: Does how members perceive their team's composition affect team processes and outcomes?

In this paper, we review the growing literature on perceived diversity in teams. We aim to clarify the construct of perceived diversity and organize the findings in this emergent line of research. To do so, we develop a framework integrating research emerging on perceived diversity from across several different research fields. We propose that the nature of perceived diversity and its effects can be best understood by identifying the focal point of the diversity perceptions being studied: perceptions of self‐to‐team dissimilarity, of subgroup splits, and of group heterogeneity. Our review concludes that perceived self‐to‐team dissimilarity and perceived subgroup splits mostly have been linked to negative effects for individuals and groups, whereas perceived group heterogeneity has been shown to exert both positive and negative effects on group outcomes. Our review also draws attention to the problem that research on perceived diversity varies not only in definitions and conceptualizations, but also in the methodological approaches towards operationalizing perceived diversity. We conclude by discussing potential areas for future research. Copyright © 2014 John Wiley & Sons, Ltd.     

Risk analysis in research environment – Part II: Weighting Lab Criticity Index using the Analytic Hierarchy Process

A new methodology for risk analysis, namely Laboratory Assessment and Risk Analysis – LARA, is proposed in the companion paper to assess risks in research/academia environment. The core of this methodology relies on defining the adequate role player factors to assess risks in research environment and their mathematical combination to quantify and assess the risk. Quantitative outcome of the analysis results in a Lab Criticity Index – LCI, constructed as a rather comprehensive function of probability, severity, risk worsening factors, research specificities and Hazard Detectability. Even though the LCI model can be used at this stage, its “surjective” and “linear” properties were outlined; the non differentiation between LCI factors remains to be solved.The present article addresses this problematic, bringing a solution based on a Multicriteria Decision Making – MCDM modeling, namely Analytic Hierarchy Process – AHP. This leads to a refined criticity index being “bijective” and unique for every combination of factors.A preliminary risk assessment based on the LARA methodology is discussed for a research lab working with lasers.     

Pharmaceuticals and other organic chemicals in selected north-central and northwestern Arkansas streams

Recently, our attention has focused on the low level detection of many antibiotics, pharmaceuticals, and other organic chemicals in water resources. The limited studies available suggest that urban or rural streams receiving wastewater effluent are more susceptible to contamination. The purpose of this study was to evaluate the occurrence of antibiotics, pharmaceuticals, and other organic chemicals at 18 sites on seven selected streams in Arkansas, USA, during March, April, and August 2004. Water samples were collected upstream and downstream from the influence of effluent discharges in northwestern Arkansas and at one site on a relatively undeveloped stream in north-central Arkansas. At least one antibiotic, pharmaceutical, or other organic chemical was detected at all sites, except at Spavinaw Creek near Mayesville, Arkansas. The greatest number of detections was observed at Mud Creek downstream from an effluent discharge, including 31 pharmaceuticals and other organic chemicals. The detection of these chemicals occurred in higher frequency at sites downstream from effluent discharges compared to those sites upstream from effluent discharges; total chemical concentration was also greater downstream. Wastewater effluent discharge increased the concentrations of detergent metabolites, fire retardants, fragrances and flavors, and steroids in these streams. Antibiotics and associated degradation products were only found at two streams downstream from effluent discharges. Overall, 42 of the 108 chemicals targeted in this study were found in water samples from at least one site, and the most frequently detected organic chemicals included caffeine, phenol, para-cresol, and acetyl hexamethyl tetrahydro naphthalene (AHTN).