Patterns of suicide mortality in England and Wales before and after the suicide of the actor Robin Williams
Bibliographic record
Abstract
PURPOSE: There is international evidence supporting an association between sensational reporting of suicide and a subsequent increase in local suicide rates, particularly where reporting the death of a celebrity. We aimed to explore whether the observed increase in suicides in the United States, Canada and Australia in the 5 months following the 2014 suicide of the popular actor Robin Williams was also observed in England and Wales. METHOD: We used interrupted time-series analysis and a seasonal autoregressive integrated moving averages (SARIMA) model to estimate the expected number of suicides during the 5 months following Williams' death using monthly suicide count data for England and Wales from the UK Office for National Statistics (ONS) 2013-2014. RESULTS: Compared with the observed 2051 suicide deaths in all age groups from August to December 2014, we estimated that we would have expected 1949 suicides over the same period, representing no statistically significant excess. CONCLUSIONS: This finding is an outlier among previous studies and contrasts with the approximately 10% increase in suicides found in similar analyses conducted in other high-income English-speaking countries with established media reporting guidelines.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".