Notice bibliographique
Résumé
The ITC Project would like to acknowledge and thank the principal investigators, researchers, staff and research assistants of the 2016 (wave 1) ITC Four Country Smoking and Vaping Survey spanning across the United States, Canada, England and Australia, who have contributed their efforts in developing the survey questions, preparing the protocols for data collection and conducting the data analysis for all papers in this supplement. Our thanks also go to the survey firms in these four countries for collecting the data. The ITC Project also wishes to acknowledge the main funding agencies that contributed to the ITC Four Country Smoking and Vaping Survey: the US National Cancer Institute (P01 CA200512), the Canadian Institutes of Health Research (FDN-148477) and the National Health and Medical Research Council of Australia (APP 1106451). Additional funding support was provided by the Ontario Institute for Cancer Research. Many thanks to Anne C. K. Quah, the ITC Managing Director and Senior Research Scientist, who led the coordination and every aspect of the organization of this excellent compilation of articles in her usual tireless way, assisted by Janine Ouimet, the project manager of the 2016 ITC Four Country Smoking and Vaping Survey. We thank K. Michael Cummings and Geoffrey T. Fong for their leadership in this project. We are grateful to the Senior Editor at Addiction for his insightful feedback on the articles in this supplement and to Molly Jarvis for coordinating the articles submission. Thanks also go out to Lalaine Bacea, the production editor, and Silvana Losito at Wiley for their excellent assistance in the production of the articles. The International Tobacco Control Policy Evaluation Project (the ITC Project) is an international research collaboration of more than 150 tobacco control researchers and experts from 29 ITC countries (Canada, United States, United Kingdom, Australia, Ireland, Thailand, Malaysia, China, Japan, Spain, Greece, Hungary, Poland, Romania, Republic of Korea, New Zealand, Mexico, Uruguay, France, Germany, the Netherlands, Brazil, Mauritius, Bangladesh, Bhutan, India, Kenya, Zambia and United Arab Emirates–Abu Dhabi) who have come together to conduct research to evaluate the impact of tobacco control policies of the WHO Framework Convention on Tobacco Control (FCTC), the world's first health treaty. These policies include more prominent warning labels (including graphic images), comprehensive smoke-free laws, restrictions or bans on tobacco advertising, promotion and sponsorship, higher taxes on tobacco products, removal of potentially deceptive labeling (e.g. ‘light’ and ‘mild’ and packaging design that lead consumers to the misperception that certain brands may be less harmful), promotion of cessation, education of the public on the harms of tobacco, reduction of illicit trade, reduction of youth access and product regulation. The ITC team in each country conducts longitudinal cohort surveys and capitalizes on natural experiments to evaluate the impact of these policies over time. ITC Surveys contain more than 150 measures of tobacco policy impact and have been conducted in countries inhabited by more than 50% of the world's population, 60% of the world's smokers and 70% of the world's tobacco users. The ITC Project has recently expanded its scope to examine the impact of policies and regulations on alternative nicotine delivery products, which is the focus of this Supplement.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,297 | 0,127 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».