Investigating the impact of parallel media engagement initiatives on suicide reporting in Canada and Israel
Bibliographic record
Abstract
Abstract Purpose To contrast changes in suicide-related media reporting quality during parallel initiatives to engage national media in Canada and Israel. Methods We coded media articles in Canada’s and Israel’s highest circulating newspapers (major broadsheet and tabloid newspapers, respectively) for putatively harmful and putatively protective suicide-related content. A sample of 150 articles (30/year) from each country was randomly selected for three time points: 2012 (T1; prior to media engagement), 2016–2017 (T2; early media engagement), and 2018–2019 (T3; late media engagement). Chi-square tests and binary logistic regression investigated overall between-country differences in reporting quality over time. Results Following media engagement, adherence to guidelines improved over time in both countries for most variables. Over time, fewer Canadian and more Israeli articles covered celebrity suicide (OR = 4.97; 95%CI 1.68–16.69); more Canadian and fewer Israeli articles covered warning signs for suicide (OR = 0.30; 95%CI 0.12–0.78). Comparing articles over the entire timespan (T1-T3), a higher proportion of Israeli tabloid articles included putatively harmful content, such as mentioning suicide means (Israel: 65.3% vs. Canada 25.3%, χ2(1) = 48.4, p < 0.001), and a higher proportion of Canadian broadsheet articles included putatively protective content, such as providing information on intervention (Israel: 2.0% vs. Canada 27.3%, χ2(1) = 38.5, p < 0.001). Conclusion Media engagement appeared to confer benefits in both countries and publication formats. A higher proportion of Canadian articles adhered to several specific recommendations. Our findings must be interpreted in the context of differences in format between major Canadian and Israeli newspapers (broadsheet vs. tabloid) and the much higher total volume of suicide-related articles in Canada.
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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 | 0.004 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".