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Record W4387378969 · doi:10.1177/00328855231200635

The “Pains of Employment”? Connecting Air and Sound Quality to Correctional Officer Experiences of Health and Wellness in Prison Space

2023· article· en· W4387378969 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Prison Journal · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsUniversity of ReginaMemorial University of Newfoundland
Fundersnot available
KeywordsPrisonOfficerFeelingSpace (punctuation)PerceptionPhysical spaceSound (geography)Quality (philosophy)PsychologyPublic relationsSocial psychologyCriminologyPolitical scienceComputer scienceAcousticsLawGeography

Abstract

fetched live from OpenAlex

This article highlights Canadian federal correctional officers’ (COs) sensory engagements with their workplace to reveal how, in particular, air quality and sound quality generate physical feelings that create health and wellness concerns. These “pains of employment” support calls to improve prison space. However, these sensations conflate with perceptions of space, which infer that prisoners, not infrastructure, create poor environments. Such perceptions seemingly influence COs’ approaches to prisoner management. Accordingly, the physical quality of prison air and sound not only shapes CO constructions of health and wellness, but also has the potential to influence how they discharge their role.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.155
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.063
GPT teacher head0.396
Teacher spread0.333 · 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