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Record W4386175731 · doi:10.1007/978-3-031-33786-4_12

Screening Workplace Disaster: The Case of Only the Brave (2017)

2023· book-chapter· en· W4386175731 on OpenAlexaff
Shane M. Dixon, Tim Gawley

Bibliographic record

VenueSpringerBriefs in applied sciences and technology · 2023
Typebook-chapter
Languageen
FieldPsychology
TopicLeadership, Courage, and Heroism Studies
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsWorkplace violenceFeature filmPublic relationsEvent (particle physics)Work (physics)Political scienceMedia studiesSociologyEngineeringPsychologyVisual artsArtSuicide preventionPoison controlMedicineMedical emergencyMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Media influence how we define and engage with our world, shaping our interpretations, attitudes, behaviours. Feature films in which work-related injuries, deaths, and disasters are the storylines can convey occupational safety messages to large, diverse audiences. Films can entertain, act as “powerful” and “poignant” memorials to workers, heighten peoples’ awareness of events, and even deepen their understanding of the causes of workplace disasters. However, it is unclear how films actually represent the complexities of workplace injury and industrial disaster. We examined the film Only the Brave (di Bonaventura, Luckinbill (Producers), Kosinski (Director) in Only the Brave [Motion Picture] (Columbia Pictures, United States, 2017)), which recounts the story of the deaths of 19 wildland firefighters in America. In particular, we examine how the film portrays workplace disaster and the factors which led up to the event. We discuss some strengths and limitations of feature films as a form of visualizing workplace disaster.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.870
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.005
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.061
GPT teacher head0.302
Teacher spread0.241 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations0
Published2023
Admission routes1
Has abstractyes

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