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Record W2757013419 · doi:10.22230/cjc.2017v42n4a3025

Dead Today, Gone Tomorrow: The Framing of Workplace Injury in Canadian Newspapers, 2009–2014

2017· article· en· W2757013419 on OpenAlex
Jason Foster, Bob Barnetson

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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Communication · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCrime, Deviance, and Social Control
Canadian institutionsAthabasca University
Fundersnot available
KeywordsNewspaperFraming (construction)HappeningFrame analysisPublic relationsPolitical scienceMedia studiesSociologyContent analysisCriminologyHistorySocial science

Abstract

fetched live from OpenAlex

Background How the media frames and presents a subject influences how society sees and responds to that issue. Analysis This study uses frame analysis to examine how Canadian English language newspapers portrayed workplace injuries between 2009 and 2014. Three frames emerge: Under Investigation, Human Tragedy, and Before the Courts. There is also a meta-frame casting injuries and fatalities as isolated events happening to “others” with no cause, thus the public ought not be concerned about workplace safety. Conclusion and implications The article concludes that media frames obscure issues of cause and fault, thereby denying workers a full understanding of why injuries happen in the workplace. These frames serve the interests of employers by obfuscating the employer’s role in creating workplace injury and death.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.701
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.021
GPT teacher head0.313
Teacher spread0.292 · 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