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Promoting Voice in Policing: The Role of Imagination, Centralization, and Psychological Safety

2022· article· en· W4283832606 on OpenAlexaffabout
Audrey Bélanger, Jean‐François Harvey

Bibliographic record

VenueAcademy of Management Proceedings · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsVoiceFeelingPsychologyContext (archaeology)Employee voiceSocial psychologyWorkforceTrait theoryPsychological safetyPublic relationsApplied psychologyPolitical scienceComputer sciencePersonalityLaw

Abstract

fetched live from OpenAlex

This article aims to trace the antecedents of promotive and prohibitive voicing in the police workforce. We draw from trait activation theory to develop a model that includes individual and organizational factors that can create or hinder the social support necessary for police officers to adopt voice behavior. Specifically, we argue feelings of psychological safety emerge and encourage voicing from imaginative individuals depending on the centralization dynamics in which they operate. We used time-lagged, survey-based data from 326 Canadian police officers to test our theory. We found that imaginative officers operating in a decentralized context exercise more voicing thanks to heightened feelings of psychological safety. However, imagination can backfire in a context of centralization because officers feel less psychologically safe and refrain from speaking out. Our study helps shed light on which officers can become inclined to engage in voice behavior and under what circumstances, which offers significant contributions to both theory and practice.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score0.348

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.037
GPT teacher head0.361
Teacher spread0.324 · 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.

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

Citations1
Published2022
Admission routes2
Has abstractyes

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