The relationship between the congruency in perceptions of coach leadership behaviours and perceptions of cohesion and performance

The purpose of the present study was to examine the relationship between perceptual congruency of coaching leadership and perceptions of cohesion and performance. Sixty coaches and 199 athletes responded to two leadership inventories: the Differentiated Transformational Leadership Inventory (DTLI; Callow et al., 2009) measuring transformational leadership and the Leadership Scale for Sports (LSS; Chelladurai &Saleh, 1980) measuring transactional leadership. Additionally, athletes indicated perceptions of cohesion by completing the Group Environment Questionnaire (GEQ; Carron et al., 1985) and perceptions of personal performance through a self-report performance measure (Spalding, 2010). Results indicated that over-evaluative athletes (i.e., those who rated the coach favourably) held greater perceptions of all four dimensions of cohesion (all p \u27s ≤ .05) and the dimension of Performance Achievement (p \u3c.001) than did under-evaluative athletes (i.e., those who rated the coach less favourably). The findings provide evidence of the role congruency has upon perceptions of the group environment

Applications of Trajectory Data From the Perspective of a Road Transportation Agency: Literature Review and Maryland Case Study

Transportation agencies have an opportunity to leverage increasingly-available trajectory datasets to improve their analyses and decision-making processes. However, this data is typically purchased from vendors, which means agencies must understand its potential benefits beforehand in order to properly assess its value relative to the cost of acquisition. While the literature concerned with trajectory data is rich, it is naturally fragmented and focused on technical contributions in niche areas, which makes it difficult for government agencies to assess its value across different transportation domains. To overcome this issue, the current paper explores trajectory data from the perspective of a road transportation agency interested in acquiring trajectories to enhance its analyses. The paper provides a literature review illustrating applications of trajectory data in six areas of road transportation systems analysis: demand estimation, modeling human behavior, designing public transit, traffic performance measurement and prediction, environment and safety. In addition, it visually explores 20 million GPS traces in Maryland, illustrating existing and suggesting new applications of trajectory data

On the Substitution of Identicals in Counterfactual Reasoning

It is widely held that counterfactuals, unlike attitude ascriptions, preserve the referential transparency of their constituents, i.e., that counterfactuals validate the substitution of identicals when their constituents do. The only putative counterexamples in the literature come from counterpossibles, i.e., counterfactuals with impossible antecedents. Advocates of counterpossibilism, i.e., the view that counterpossibles are not all vacuous, argue that counterpossibles can generate referential opacity. But in order to explain why most substitution inferences into counterfactuals seem valid, counterpossibilists also often maintain that counterfactuals with possible antecedents are transparency‐preserving. I argue that if counterpossibles can generate opacity, then so can ordinary counterfactuals with possible antecedents. Utilizing an analogy between counterfactuals and attitude ascriptions, I provide a counterpossibilist‐friendly explanation for the apparent validity of substitution inferences into counterfactuals. I conclude by suggesting that the debate over counterpossibles is closely tied to questions concerning the extent to which counterfactuals are more like attitude ascriptions and epistemic operators than previously recognized

Ecological Response to Extreme Flow Events in Streams and Rivers: Implications of Climate Change for Aquatic Biodiversity

We used the USEPA\u27s 2008-2009 National Rivers and Streams Assessment (NRSA) data to assess the potential sensitivity of stream biodiversity to both spatial variation in measures of extreme flow and likely changes in extreme flows associated with projected climate change. The NRSA data consisted of macroinvertebrate samples collected at 1313 reference-quality sites. We characterized the hydrologic regimes at each of these sites by developing Random Forest empirical models from long-term (≥ 20 years) daily flow records obtained from 601 gaged USGS stations. These models described spatial variation in 16 flow variables as a function of climate and watershed attributes. Three of the models characterized aspects of extreme flow: the mean number of zero-flow events per year (ZeroDays), the mean number of high-flow events per year (HighDays = number of events per year that exceed the 95th percentile of mean annual flow), and the coefficient of variation of daily flows (CV). We used these models to predict the flow attributes expected at each of the 1313 sites with ecological data. We then built additional Random Forest models that related among-site differences in stream macroinvertebrate taxonomic composition, assemblage richness, and the likelihood of observing individual taxa to the 16 measures of flow regime and other environmental predictors. At the national level, ZeroDays was an important predictor of macroinvertebrate biodiversity: richness declined as ZeroDays increased. A similar pattern was observed when analyses were restricted to lowland and plains streams. For eastern highland streams, HighDays was a better predictor of stream biodiversity than aspects of low flow: richness declined as HighDays increased. For western streams, CV was a better predictor of biodiversity than either ZeroDays or HighDays: biodiversity decreased as CV increased. Empirical models that linked flow attributes to climate change projections imply that flow regime response to climate change will vary nationally with many currently intermittent streams becoming more permanent and many permanent streams becoming more intermittent. Ecological responses to climate change are therefore expected to exhibit similar idiosyncratic patterns with some streams losing biodiversity and other streams gaining biodiversity