Suicide portrayal in the Canadian media: examining newspaper coverage of the popular Netflix series ‘13 Reasons Why’
Bibliographic record
Abstract
BACKGROUND: Evidence suggests that the media can influence societal attitudes and beliefs to various social issues. This influence is especially strong for mental health issues, particularly suicide. As such, the aim of this study is to systematically examine Canadian newspaper coverage of the popular fictional Netflix series 13 Reasons Why, wherein the lead character dies by suicide in the final episode. METHODS: Articles mentioning the series were systematically collected from best-selling Canadian newspapers in the three-month period following series release (April-June 2017). Articles were coded for adherence to key best practice recommendations on how to sensitively report suicide. Frequency counts and proportions were produced. An inductive qualitative thematic analysis was then undertaken to identify common themes within the articles. RESULTS: A total of 71 articles met study inclusion criteria. The majority of articles did not mention the suicide method (88.7%) and did not use stigmatizing language such as 'commit suicide' (84.5%). Almost half of the articles linked suicide to wider social issues (43.7%) or quoted a mental health professional (45.1%). 25% included information telling others considering suicide where to get help. Our qualitative analysis indicated that articles simultaneously praised and criticized the series. It was praised for (i) promoting dialogue and discussion about youth suicide; (ii) raising awareness of youth suicide issues; (iii) shining a spotlight on wider social issues that may affect suicide. It was criticized for (i) glorifying suicide, (ii) harmfully impacting young viewers; (iii) prompting pushback from educators and schools. CONCLUSIONS: Newspaper coverage of '13 Reasons Why' generally adhered to core best practice media recommendations, and sensitively discussed suicide from various angles, prompting productive discussion and dialogue about youth suicide. These findings suggest that the media can be an ally in promoting dialogue and raising awareness of important public health issues such as suicide.
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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 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.017 | 0.024 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".