820 resultados para Career concerns


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Northumbria University final Jisc-ARMA ORCID pilot summary

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Technology for employability: HE case studies

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With the increasing recognition that climate change is occurring and having large impacts on living marine resources, a sound ecosystem approach to management of those resources requires both understanding how climate affects ecosystems and integration of that understanding into management processes. The National Marine Fisheries Service (NMFS) must identify how changing climatic conditions will impact its mission and must be prepared to adapt to these changes. This document identifies the climate related ecosystem concerns in the regional marine ecosystems for which NMFS has living marine resource management responsibilities, what NMFS is currently doing to address these concerns, what NMFS must do going forward to address these concerns, and what climate information is needed to integrate climate into resource management. The regional ecosystems included in this analysis are: the Northeast U.S. Continental Shelf; the Southeast U.S. Continental Shelf, Gulf of Mexico, and U.S. Caribbean; the California Current Ecosystem; the Alaskan Ecosystem Complex; the Pacific Island Ecosystem Complex; the Eastern Tropical Pacific; North Pacific Highly Migratory Species; and the Antarctic.

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The PIC model by Gati and Asher describes three career decision making stages: pre-screening, in-depth exploration, and choice of career options. We consider the role that three different forms of support (general career support by parents, emotional/instrumental support, and informational support) may play for young adults in each of these three decision-making stages. The authors further propose that different forms of support may predict career agency and occupational engagement, which are important career decision precedents. In addition, we consider the role of personality traits and perceptions (decision-making window) on these two outcomes. Using an online survey sample (N = 281), we found that general career support was important for career agency and occupational engagement. However, it was the combination of higher general career support with either emotional/instrumental support or informational support that was found to lead to both greater career agency and higher occupational engagement. Personality also played a role: Greater proactivity also led to greater occupational engagement, even when there was little urgency for participants to make decisions (window of decision-making was wide open and not restricted). In practical terms, the findings suggest that the learning required in each of the three PIC processes (pre-screening, in-depth exploration, choice of career options may benefit when the learner has access to the three support measures.

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Wylleman, P., Alfermann, D., Lavallee, D. (2004). Career transitions in sport: European perspectives. Psychology of Sport and Exercise, 5 (1), 7-20 RAE2008

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Lavallee, D. (2005). The effect of a life development intervention on sports career transition adjustment. The Sport Psychologist. 19(2), pp.193-202 RAE2008

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North, J., Lavallee, D., An investigation of potential users of career transition services in the United Kingdom, Psychology of Sport and Exercise, Vol. 5, No. 1. (January 2004), pp. 77-84. RAE2008

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One relatively unexplored question about the Internet's physical structure concerns the geographical location of its components: routers, links and autonomous systems (ASes). We study this question using two large inventories of Internet routers and links, collected by different methods and about two years apart. We first map each router to its geographical location using two different state-of-the-art tools. We then study the relationship between router location and population density; between geographic distance and link density; and between the size and geographic extent of ASes. Our findings are consistent across the two datasets and both mapping methods. First, as expected, router density per person varies widely over different economic regions; however, in economically homogeneous regions, router density shows a strong superlinear relationship to population density. Second, the probability that two routers are directly connected is strongly dependent on distance; our data is consistent with a model in which a majority (up to 75-95%) of link formation is based on geographical distance (as in the Waxman topology generation method). Finally, we find that ASes show high variability in geographic size, which is correlated with other measures of AS size (degree and number of interfaces). Among small to medium ASes, ASes show wide variability in their geographic dispersal; however, all ASes exceeding a certain threshold in size are maximally dispersed geographically. These findings have many implications for the next generation of topology generators, which we envisage as producing router-level graphs annotated with attributes such as link latencies, AS identifiers and geographical locations.