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.
Bibliographic record
Abstract
The 2016 film Deepwater Horizon offers a rare portrayal of industrial disaster. It is novel as there are few film-based treatments of this issue. The film enables the public to learn about the disaster, the lives lost, and the stories of survival, but it also provides the opportunity to examine how industrial disaster and, by extension, occupational health and safety may be publicly framed and understood. This article presents an analysis of Deepwater Horizon. Four primary industrial disaster frames are identified in the film: profit maximization, technology and technology failure, managerial conflict, and worker portrayals. Each frame offers advantages and limitations for enhancing public understandings of industrial disaster. Missing from the film is the regulatory environment of the oil drilling industry, whose omission serves to potentially reproduce messages that privilege individualistic, isolated, views of industrial disasters and prioritize immediate over distal causes.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it