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Record W2146538825 · doi:10.1177/0093854803254432

Police Work, Burnout, and Pro-Organizational Behavior

2003· article· en· W2146538825 on OpenAlexaff
Andrea Kohan, Dwight Mazmanian

Bibliographic record

VenueCriminal Justice and Behavior · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsLakehead University
Fundersnot available
KeywordsBurnoutPsychologyOrganizational citizenship behaviorCoping (psychology)Social psychologyOrganizational commitmentPerceptionAffect (linguistics)Clinical psychology

Abstract

fetched live from OpenAlex

This study assessed officers' perceptions of daily work experiences (operational and organizational) and the nature of their associations with burnout and pro-organizational behavior (organizational citizenship behavior [OCB]). The moderating and mediating effects of dispositional affect and coping style were also considered. Findings showed that (a) appraisals of negative experiences (hassles) depended on frequency of exposure to the different facets of work, whereas positive organizational experiences (uplifts) were perceived as being more uplifting than operational ones; (b) burnout and OCB were more strongly associated with organizational experiences than with operational ones; and (c) only problem- and emotion-focused coping moderated, but did not mediate, associations, suggesting that chronic exposure to stressful events may act independently of disposition and that both coping styles may be beneficial.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.262
Teacher spread0.235 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations88
Published2003
Admission routes1
Has abstractyes

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