Pygmalion in work organizations: a meta‐analysis

The Pygmalion effect, a type of self‐fulfilling prophecy, has been demonstrated in educational settings with empirical studies, qualitative reviews and meta‐analyses. It has also been studied in organizational settings. This meta‐analysis provides a review of the Pygmalion literature, an analysis of findings to date, and a deeper look into the nature of the effect. The present analysis of 13 effect sizes revealed an overall d for the Pygmalion effect in work organizations of 0.81. Moderator analyses revealed stronger effects when the initial level of performance was low and when the experiment took place in a military rather than a business setting. Implications of these findings are discussed. Copyright © 2000 John Wiley & Sons, Ltd.     

Personality and job performance: the importance of narrow traits

In a recent discussion of the bandwidth–fidelity dilemma in personality measurement for personnel selection, Ones and Viswesvaran (1996) concluded that ‘broader and richer personality traits will have higher predictive validity than narrower traits’. In this paper, the arguments made by Ones and Viswesvaran in favor of the exclusive use of broad personality dimensions are discussed. New data are presented that contradict Ones and Viswesvaran's claim of the existence of a general, integrity-related personality factor, and that show two narrow measures—the Responsibility and Risk Taking scales of the Jackson Personality Inventory—to have higher validities than the Big Five dimensions with respect to job performance criteria based on self-reported workplace delinquency in a sample of 127 entry-level employees. © 1998 John Wiley & Sons, Ltd.     

Enhancing perspectives on lake impairments using satellite observations: A case study on High Rock Lake,North Carolina

Stakeholders developing water quality improvement plans for lakes and reservoirs are challenged by the sparsity of in-situ data and the uncertainty ingrained in management decisions. This study explores how satellite images can fill gaps in water quality databases and provide more holistic assessments of impairments. The study site is an impaired water body that is serving as a pilot for improving state-wide nutrient management planning processes. An existing in-situ database was used to calibrate semi-analytical models that relate satellite reflectance values to turbidity and total suspended solids (TSS). Landsat-7 images from 1999 to 2020 that overpass High Rock Lake, North Carolina were downloaded and processed, providing 42 turbidity and 39 TSS satellite and in-situ match-ups for model calibration and validation. Model r-squared values for the fitted turbidity and TSS models are 0.72 and 0.74, and the mean absolute errors are 14.6 NTU and 3.2 mg/L. The satellite estimates were compared to the in-situ data and simulated TSS values produced by a calibrated hydrologic-hydrodynamic model. The process-based model is considered less accurate than the satellite model based on statistical performance metrics. Comparisons between data sources are illustrated with time series plots, frequency curves, and aggregate decision metrics to highlight the dependence of lake impairment assessments on the spatial and temporal frequency of available data and model accuracy.     

Model‐Based Nitrogen and Phosphorus (Nutrient) Criteria for Large Temperate Rivers: 2. Criteria Derivation

Nitrogen and phosphorus criteria were developed for 233 km of the Yellowstone River, one of the first cases where a mechanistic model has been used to derive large river numeric nutrient criteria. A water quality model and a companion model which simulates lateral algal biomass across transects were used to simulate effects of increasing nutrients on five variables (dissolved oxygen, total organic carbon, total dissolved gas, pH, and benthic algal biomass in depths ≤1 m). Incremental increases in nutrients were evaluated relative to their impact on predefined thresholds for each variable; the first variable to exceed a threshold set the nutrient criteria. Simulations were made at a low flow, the 14Q5 (lowest average 14 consecutive day flow, July‐September, recurring one in five years), which was derived using benthic algae growth curves and EPA guidance on excursion frequency. An extant climate dataset with an annual recurrence was used, and tributary water quality and flows were coincident with the river's 10 lowest flow years. The river had different sensitivities to nutrients longitudinally, pH being the most sensitive variable in the upstream reach and algal biomass in the lower. Model‐based criteria for the Yellowstone River are as follows: between the Bighorn and Powder river confluences, 55 μg TP/l and 655 μg TN/l; from the Powder River confluence to Montana state line, 95 μg TP/l and 815 μg TN/l. Pros and cons of using steady‐state models to derive river nutrient criteria are discussed.