Coverage of Robin Williams' Suicide in Australian Newspapers
Bibliographic record
Abstract
Abstract. Background: Australia's Mindframe guidelines provide media professionals with advice on ways to safely report on suicide. Aims: We aimed to examine the extent to which Australian newspaper articles on Robin Williams' suicide conformed to the Mindframe recommendations. Method: We searched Factiva for relevant articles appearing in Australian newspapers during the 5 months following Williams' death on August 11, 2014. We retrieved the text of these articles from Factiva and, wherever possible, sourced scanned copies from the National Library of Australia. Trained coders rated the articles for quality, using a 10-item coding framework derived from the Mindframe guidelines. Results: Our search yielded 303 articles. In general, there were high levels of adherence to the Mindframe guidelines, with 67% of articles adhering to at least eight (80%) of the Mindframe guidelines. Limitations: We may have missed some articles and the coders' task involved some subjective judgments. Conclusion: Australian newspaper reporting of Robin Williams' suicide was largely consistent with the Mindframe guidelines. In particular, there was good adherence to recommendations designed to minimize the risk of imitative acts, which is positive. The poorer performance of articles in terms of recommendations to do with public education about suicide may be a missed opportunity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".