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Record W4383228147 · doi:10.1111/1745-9125.12346

Correctional officers and the use of force as an organizational behavior

2023· article· en· W4383228147 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCriminology · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsMacEwan University
FundersKillam TrustsSocial Sciences and Humanities Research Council of CanadaUniversity of CambridgeUniversity of AlbertaPierre Elliott Trudeau Foundation
KeywordsManagerialismPrisonBureaucracyInterpretation (philosophy)NegotiationDisciplineUse of forceOrder (exchange)Public relationsCriminologyPolitical sciencePsychologyPublic administrationBusinessLawComputer science

Abstract

fetched live from OpenAlex

Abstract During the past 30 years, bureaucratic managerialism has reshaped how prison staff maintain order. Policies and graduated disciplinary models have replaced coercive methods, reducing disciplinary use of force by prison staff against incarcerated people. Managerialism, however, disguises deep problems in the interpretation and enforcement of use‐of‐force policies. Drawing on 131 semistructured interviews with Canadian correctional officers (COs), I show how managers and prison staff interpret and negotiate policies to justify using force to maintain order. Although COs frame policies and management supervision as significant checks on their actions, they also suggest that inconsistencies in policy interpretation and implementation facilitate certain kinds of use‐of‐force decisions, which I define as “construction” and “outsourcing.” I conclude by discussing the broader organizational implications of these findings.

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.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.761
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.127
GPT teacher head0.347
Teacher spread0.220 · 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