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Record W2886730464 · doi:10.1093/police/pay057

Driving as an Under-acknowledged Risk in Rural Policing

2018· article· en· W2886730464 on OpenAlexaffabout
Rosemary Ricciardelli, Dale Spencer, Elizabeth Andres

Bibliographic record

VenuePolicing A Journal of Policy and Practice · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsMemorial University of NewfoundlandCarleton University
Fundersnot available
KeywordsDutyHuman factors and ergonomicsOccupational safety and healthPoison controlCriminologyPsychologyBusinessPolitical sciencePublic relationsEnvironmental healthMedicineLaw

Abstract

fetched live from OpenAlex

Abstract One topic rarely discussed in the policing literature is driving-related accidents, injuries, and deaths, despite the fact that, for example, such deaths vastly outnumber gun-related fatalities for officers on active duty. There is even less literature on automobile-related incidents and deaths in relation to rural policing. Based on 14 focus groups with police officers (n = 49) across a primarily rural Canadian province, we probe the various driving-related risks faced by these officers. Drawing from the literature on automobility, we examine the various aspects of driving that place officers at risk of fatality. We highlight the driving-related occupational risks specific to rural policing and how such risks inhibit their ability to conduct their jobs safely and effectively. We conclude with policy implications and avenues for future research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.480
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.003
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.058
GPT teacher head0.458
Teacher spread0.400 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2018
Admission routes2
Has abstractyes

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