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Enregistrement W2323562903

Generations of training.

2004· editorial· en· W2323562903 sur OpenAlexaboutno aff
James P. Waddell

Notice bibliographique

RevuePubMed · 2004
Typeeditorial
Langueen
DomaineHealth Professions
ThématiqueDental Education, Practice, Research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésWonderMedicineMedical educationLoyaltyTraining (meteorology)PsychologySocial psychologyMarketing
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Two recent academic events came together in what might be considered a synergistic fashion and caused me to consider once again the issues around surgical training in Canada in the further light of our ability to deliver appropriate care in the community by ensuring that Canadian trainees are given appropriate exposure to good teaching and good clinical experience. I was recently asked to give a talk on generational differences among physicians and how this affects orthopedic surgery. At much the same time we were conducting, within our own Division of Orthopaedic Surgery at the University of Toronto, a faculty development exercise on the strengths and attributes in trainees that would ensure success in later practice. Trainees were asked as well what they felt they needed in their training program to ensure their success during their residency, with the Royal College evaluation process and finally in clinical practice. The research around generational differences has revealed that “Gen Xers” — members of the so-called Generation X — enjoy unprecedented mobility, a healthy suspicion of authority, a lack of institutional loyalty and a readiness to look at every alternative rather than simply accepting what they are told or taught.1,2 Many of the characteristics of current trainees that we find so difficult I think reflect the generational difference in attitude toward work, authority and commitment. Although many of us wonder why residents nowadays are not “more like we used to be,” it is my impression that the trainees are probably wondering the same thing about us: Why aren't we more like them? This impression was buttressed by the survey we took about resident attributes. The dozens of responses we received basically expressed 5 themes, which might be termed honesty, dedication, intellectual curiosity, technical ability and capacity for hard work. Most will all agree that these in fact are characteristics amply demonstrated by our trainees, and no different from the qualities we had as trainees and hope to continue to retain as practising surgeons. When residents what they wanted or liked in their training program, the replies were equally predictable: courteous and helpful nursing staff, dedicated attending staff, good lectures and didactic teaching, ample access to instruction about procedures and a caring and committed faculty. What they don't want are teachers who blame the trainee for procedural inadequacies or the hospital in which they work for deficiencies, or who cannot accept the inevitable change in education that is occurring all around us. The lesson I learned was that there exists no great discrepancy between what the teachers and the taught feel they need in order to be successful. There is no shortage of opportunity for trainees to obtain what they need to feel comfortable about what they are learning now and what they will practise in future. The people who teach should be sensitive to the generational differences that make current trainees seem less involved or engaged in the exercise of learning, and recognize that our current residents' commitment to excellence is no less than was ours when we were learning our craft. James P. Waddell, MD Coeditor

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,013
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,025
Score d'incertitude au seuil0,998

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,013
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,156
Tête enseignante GPT0,487
Écart entre enseignants0,331 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2004
Routes d'admission1
Résumé présentoui

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