Injury and Injustice
In: Annual Review of Law and Social Science, Band 16, S. 241-256
9985 Ergebnisse
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In: Annual Review of Law and Social Science, Band 16, S. 241-256
SSRN
In: Military behavioral health, Band 6, Heft 2, S. 119-120
ISSN: 2163-5803
In: Social analysis: journal of cultural and social practice, Band 61, Heft 4
ISSN: 1558-5727
In: Malingering, Feigning, and Response Bias in Psychiatric/ Psychological Injury; International Library of Ethics, Law, and the New Medicine, S. 535-566
In: Labor: studies in working-class history of the Americas, Band 2, Heft 1, S. 143-144
ISSN: 1558-1454
In: Veterans' Policies, Veterans' Politics, S. 65-88
In: Australian quarterly: AQ, Band 59, Heft 1, S. 119
ISSN: 1837-1892
In: How Policy Shapes Politics, S. 152-189
In: How Policy Shapes Politics, S. 108-151
In: Contexts / American Sociological Association: understanding people in their social worlds, Band 11, Heft 1, S. 59-61
ISSN: 1537-6052
Cyber communities have facilitated new forms of identity and self-regulation for people engaging in self-harm practices. The authors explore the online worlds of self-injurers and how they offer ways for people to develop new kinds of social order.
In: http://hdl.handle.net/2027/uiug.30112058635530
Shipping list no.: 2004-0103-P. ; Title missing on cover. ; Mode of access: Internet.
BASE
In: http://hdl.handle.net/2027/uiug.30112048195678
Shipping list no.: 2002-0058-P. ; Cover title. ; Mode of access: Internet.
BASE
In: 59 WM. & MARY L. REV. 2285 (2018)
SSRN
In: Decision sciences, Band 50, Heft 2, S. 374-409
ISSN: 1540-5915
ABSTRACTInjuries are the primary determinant of an individual's mobility, which affect not just their workplace productivity in intensive environments such as manufacturing, but also their decision‐making ability and quality of life. Managers typically assign workers to projects or tasks without having knowledge about their functional capabilities or current state of injury risk as injuries remain highly underreported at workplaces for fear of reprisal and other reasons. Therefore, high‐quality research on injury prevention is nearly nonexistent. Procedures that we use in this study for developing a prediction model for identification of college football players at an elevated injury risk could also be used to quantify injury risk in various occupational settings. Using a number of measurements and models, we arrive at an estimate of an individual's injury likelihood. Our measures include ratings of movement efficiency through physical performance tests, acceleration using Internet of Things (IoT) devices, functional role classifications, and recorded exposures to high‐risk conditions. Findings prescribe several approaches and decision rules for prediction of injury risk and suggest that training programs need to consider an individual's injury risk rather than offer a 'one‐size‐fits‐all' approach. The analytics models derived from a combination of injury risk screening and surveillance data can be used for making decisions about targeting employee‐centric risk‐reduction interventions, improved matching of tasks to individuals, or deciding job rotation for improved performance, all while enhancing the quality of life of individuals and reducing the escalating costs of work‐related injuries borne by employers. These models can also be developed for smartphones.