Stigmatisation et santé publique : le côté obscur des interventions anti-tabac
Bibliographic record
Abstract
Tobacco control strategies, considered legitimate and effective, are rarely the subject of critical analysis in France. This is specifically true with regard to their potentially harmful effects, particularly against people who continue to smoke. This article introduces this debate, focusing on the potentially stigmatizing effects of anti-smoking policies. It has been attested by numerous international studies, and by a study in France, that the general process of tobacco denormalization has led to the stigmatization of smokers who then may be subject to discrimination. To the extent that smoking is now concentrated in the most disadvantaged socio-economic populations in France, the latter are thus more exposed to stigma. While underscoring the need to develop targeted interventions against them, this article also warns and calls for vigilance regarding the potential iatrogenic effects of these interventions. It is therefore necessary to develop research and evaluations on this subject in order to accurately measure the effects of these interventions, particularly in terms of stigmatization and self-stigma, and to ensure that public health actors do not generate more problems than they solve.
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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 | 0.020 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".