In Reply to Rosenkranz and Hu and to Wolfson and Arora
Notice bibliographique
Résumé
We appreciate the thoughtful commentary on our review, provided by Rosenkranz and Hu and by Wolfson and Arora. Here, we will attempt to clarify a few points from our review1 that were discussed in these letters. Rosenkranz and Hu caution that some items (including self-reported medical student research participation and publication rates) discussed in our review may reflect selection bias, and that our recommendation to increase curricular time devoted to medical student research may not be suitable for every institution, given resource constraints. Selection bias should be considered when interpreting voluntary survey data, particularly regarding extracurricular initiatives. Students choosing to participate in extracurricular research activity may value research differently than the entire medical student population. We did not necessarily suggest that medical education programs invest more (of already limited) formal, curricular time in medical student research. Rather, we suggested that giving students the option of extending their (often extracurricular) research project timeline could provide a more fulfilling, robust scholarship experience to the select students who voluntarily choose this option. Allowing for greater time would also address factors (such as mentor interaction and time available to devote to the project) frequently cited in student feedback regarding the research programs reviewed as well as our own 10-week Summer Studentship Program at the University of Ottawa.2 More time for research may also lead to more mature research products, facilitating increased dissemination rates, thereby addressing student desire to be recognized for their scholarly contributions. We do agree that research program duration should be consistent with an institution’s available resources, including dedicated research mentors. Ultimately, local participant feedback should also be considered when optimizing program time duration. Wolfson and Arora suggested that using publication metrics to assess medical student research programs may be inconvenient and proposed relying on more immediate measures, including whether research programs positively impacted student attitudes towards future research activity. However, many reviewed studies have already assessed this; our review and our local program evaluation study both described that students generally perceive their research experience positively and self-report increased interest in future research activity.1,2 What is not clear is whether this self-reported, perceived interest in future research is typically realized as future research contributions. Given that the average time to publication is less than 16 months in our local research program,2 tracking dissemination outcomes may be an achievable short-term metric to evaluate these programs, complementing the student feedback that is typically collected. Long-term, tracking actual future research activity may provide more tangible information than the “intent” to conduct research, for the purposes of program evaluation. Christopher J. Ramnanan, PhD Assistant professor, Department of Innovation in Medical Education, University of Ottawa Faculty of Medicine, Ottawa, Ontario, Canada; [email protected] Youjin Chang, MD Resident, Department of Surgery, University of Ottawa Faculty of Medicine, Ottawa, Ontario, Canada.
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 | 0,029 | 0,236 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,004 | 0,003 |
| Bibliométrie | 0,004 | 0,005 |
| Études des sciences et des technologies | 0,004 | 0,006 |
| Communication savante | 0,008 | 0,011 |
| Science ouverte | 0,007 | 0,006 |
| Intégrité de la recherche | 0,035 | 0,041 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,009 |
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 ».