Will web-based research suffice when collecting U.S. school district policies? The case of physical education and school-based nutrition policies
Notice bibliographique
Résumé
BACKGROUND: Recognizing the growing childhood overweight problem, a number of school-based strategies, including policy approaches, have been proposed and are being implemented to address the problem considering the amount of time children spend in schools. This paper describes the results of a pilot study that tested approaches to collecting U.S. school district policy information regarding physical education and nutrition requirements that can inform efforts by policy makers, researchers, advocates and others interested in collecting school district-level obesity-related policies that are typically not systematically available from a "one stop" source. METHODS: Sixty local school districts representing six states were selected for conducting the district policy research, with larger, urban school districts over-sampled to facilitate collection of policies from districts representing a larger proportion of the public school population in each study state. The six states within which the pilot districts were located were chosen based on the variability in their physical education and school-based nutrition policy and geographic and demographic diversity. Web research and a mail canvass of the study districts was conducted between January and May 2006 to obtain all relevant policies. An additional field collection effort was conducted in a sample of districts located in three study states to test the extent to which field collection would yield additional information. RESULTS: Policies were obtained from 40 (67%) of the 60 districts, with policies retrieved via both Web and mail canvass methods in 16 (27%) of the districts, and were confirmed to not exist in 10 (17%) of the districts. Policies were more likely to be retrieved from larger, urban districts, whereas the smallest districts had no policies available on the Web. In no instances were exactly the same policies retrieved from the two sources. Physical education policies were slightly more prevalent than nutrition policies. CONCLUSION: Collection of U.S. local school district policies requires a multi-pronged approach. Web research and mail canvasses will likely yield different types of policy information. Given the variance in district-level Web site presence, researchers and others interested in obtaining district physical education and nutrition-related policies should consider supplementing Web research with more direct methods.
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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 | 0,216 | 0,338 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,007 | 0,018 |
| Études des sciences et des technologies | 0,006 | 0,005 |
| Communication savante | 0,013 | 0,017 |
| Science ouverte | 0,003 | 0,005 |
| Intégrité de la recherche | 0,004 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».