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Record W4365146397 · doi:10.1177/17416590231168337

News media framing of correctional officers: “Corrections is so Negative, we don’t get any Good Recognition”

2023· article· en· W4365146397 on OpenAlexaffabout
Rosemary Ricciardelli, Mark C. J. Stoddart, Heather Austin

Bibliographic record

VenueCrime Media Culture An International Journal · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsFraming (construction)MainstreamMedia studiesNarrativeNews mediaPerceptionSociologyPublic relationsSocial psychologyPsychologyPolitical scienceLawHistoryArtLiterature

Abstract

fetched live from OpenAlex

The work of correctional officers (COs) is essential yet remains largely hidden from society. As such, media framing plays an important role in shaping public perceptions of COs and their work. COs encounter adverse events over the course of their occupational work and are legally—and sometimes publicly—held accountable. In the current study, we first present a text-based frame analysis of local news media published between January 2019 and December 2019 to see how COs are represented in the province of Newfoundland and Labrador (NL). We then draw from 25 interviews with COs employed at Her [His] Majesty’s Penitentiary in St. John’s, NL, to learn how the officers interpret the media’s framing of their occupation. Grounded emergent theme analyses of interview data reveal officers share concerns about what they perceived as unfair negative media framing. COs more often feel like objects of media framing with little agency to shape media narratives about their work. COs’ lay theories about their representation in mainstream news media illuminate a misalignment between media framing and their own work experience. This misalignment is a source of anxiety and additional job strain.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.050
GPT teacher head0.347
Teacher spread0.297 · 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

Citations21
Published2023
Admission routes2
Has abstractyes

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