Notice bibliographique
Résumé
Dear Editor-in-Chief I read with interest the recent article of Syväoja et al. (4) showing that although the self-reported physical activity of 12-yr-old children was directly associated with teacher gradings of academic attainment, uniaxial accelerometer measurements of daily physical activity did not show such an association. One potential issue is the accuracy of self-reports. Many children substantially overestimate their absolute levels of physical activity (2). Nevertheless, most authors would accept that questionnaires are capable of ranking interindividual differences in habitual physical activity and, thus, of demonstrating correlations between habitual activity and other variables such as academic attainment. A uniaxial accelerometer provides the observer with objective data, but there are several pitfalls to accurate interpretation of activity counts. Syväoja et al. (4) based their analysis upon students who provided at least 500 min of data on each of two weekdays and one weekend day. However, a much larger volume of information is needed to provide an accurate picture of a person’s activity over an entire year (5). Furthermore, if the device is worn for only a short period, reactive effects may lead to an upward skewing of readings in a proportion of the students (1). Moreover, the accelerometer underestimates or fails to record many childhood activities. Syväoja et al. (4) note skateboarding, but one may add swimming and cycling, to the list of poorly identified activities. Finally, and perhaps most critically, activity counts are averaged over the entire day, whereas in terms of academic learning, the critical factor may be the intervention of a period of vigorous activity during the time that the child is attending school. Syväoja et al. (4) suggest that their study is the first to look at relations between objectively measured physical activity and academic performance. In terms of accelerometer measurements, they are correct. However, an alternative approach to this question is to impose a substantial and known fraction of the child’s daily physical activity through an hour of vigorous daily classroom activity, using a quasi-experimental design. The Trois Rivières study carried out such an investigation for a 6-yr period and thus demonstrated that children who received a daily hour of added specialist-taught physical activity had a better level of academic achievement than their peers who received only a nominal weekly amount of physical education from their homeroom teachers, whether their performance was determined by local classroom appraisals or by province-wide examinations (3). In conclusion, our quasi-experimental study would seem to support the questionnaire rather than the accelerometer data. Moreover, given the known arousing effect of physical activity, one important variable to consider in all future research on this topic would seem to be the time relationships between periods of physical activity and academic instruction. No funding was received for this study, and there is no conflict of interest.
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 | 0,003 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,005 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,003 |
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 ».