Overcoming the Unhealthy Pursuit of Thinness: Reaction to the Québec Charter for a Healthy and Diverse Body Image
Bibliographic record
Abstract
OBJECTIVES: We examined the population reach, acceptability, and perceived potential of an initiative that developed a promotional tool for a healthy body image, the Québec Charter for a Healthy and Diverse Body Image. The Charter, developed through consensus building by a multisectoral, government-led task force, outlined actions to be undertaken by organizations or citizens to reduce media pressures favoring thinness. METHODS: Six months after the Charter's launch, we surveyed 1003 Québec residents aged 18 years or older about their knowledge of the Charter, their willingness to adhere to it, and their perceptions of its potential. RESULTS: After minimal prompting, more than 35% of respondents recognized the Charter. About 33.7% were very favorable toward personally adhering to the Charter and 32.7% perceived the Charter as having high potential to sensitize people to negative consequences of disordered eating. Women showed greater likelihood and people with lesser education showed lower likelihood of spontaneous recognition. CONCLUSIONS: An initiative involving the creation of a body image Charter reaches a substantial portion of adults and is viewed as acceptable and potentially influential.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".