Cross‐national perspectives about weight‐based bullying in youth: nature, extent and remedies
Bibliographic record
Abstract
BACKGROUND: No cross-national studies have examined public perceptions about weight-based bullying in youth. OBJECTIVES: To conduct a multinational examination of public views about (i) the prevalence/seriousness of weight-based bullying in youth; (ii) the role of parents, educators, health providers and government in addressing this problem and (iii) implementing policy actions to reduce weight-based bullying. METHODS: A cross-sectional survey of adults in the United States, Canada, Iceland and Australia (N = 2866). RESULTS: Across all countries, weight-based bullying was identified as the most prevalent reason for youth bullying, by a substantial margin over other forms of bullying (race/ethnicity, sexual orientation and religion). Participants viewed parents and teachers as playing major roles in efforts to reduce weight-based bullying. Most participants across countries (77-94%) viewed healthcare providers to be important intervention agents. Participants (65-87%) supported government augmentation of anti-bullying laws to include prohibiting weight-based bullying. Women expressed higher agreement for policy actions than men, with no associations found for participants' race/ethnicity or weight. Causal beliefs about obesity were associated with policy support across countries. CONCLUSIONS: Across countries, strong recognition exists of weight-based bullying and the need to address it. These findings may inform policy-level actions and clinical practices concerning youth vulnerable to weight-based bullying.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".