Trends in Newspaper Coverage of Mental Illness in Canada: 2005–2010
Bibliographic record
Abstract
OBJECTIVES: Much research suggests that the general public relies on the popular media as a primary source of information about mental illness. We assessed the broad content of articles relating to mental illness in major Canadian newspapers over a 6-year period. We also sought to assess if such content has changed over time. METHODS: We conducted a retrospective analysis of Canadian newspaper coverage from 2005 to 2010. Research assistants used a standardized guide to code 11 263 newspaper articles that mention the terms mental health, mental illness, schizophrenia, or schizophrenic. Once the articles were coded, descriptive statistics were produced for overarching themes and time trend analyses from 2005 to 2010. RESULTS: Danger, violence, and criminality were direct themes in 40% of newspaper articles. Treatment for a mental illness was discussed in only 19% of newspaper articles, and in only 18% was recovery or rehabilitation a significant theme. Eighty-three per cent of articles coded lacked a quotation from someone with a mental illness. We did not observe any significant changes over time from 2005 to 2010 in any domain measured. CONCLUSION: There is scope for more balanced, accurate, and informative coverage of mental health issues in Canada. Newspaper articles infrequently reflect the common realities of mental illness phenomenology, course, and outcome. Currently, clinicians may direct patients and family members to other resources for more comprehensive and accurate information about mental illness.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.016 | 0.026 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".