Notice bibliographique
Résumé
To the Editor: Being a learner in medicine can feel like being in a constant—and sometimes disillusioning—state of catch-up. My relationship with learning in medical school was fragile. I questioned the superficial mnemonics, the esoteric medical trivia, the fascination with minutiae—medallions of competence that amplified knowledge differentials between neophytes and experts. There was too much fragmented information, often received all at once and sometimes lacking in clinical relevance. This knowledge felt like a privileged exorbitant excess that I struggled to master even as I finished medical school. Then, suddenly, we all became learners during the COVID-19 pandemic. When everyone knows very little about a disease, there is a peculiar equalization between the novice trainee and the expert clinician. Sheltered at home, I observed how medical journals and discussions became unusually lively and diverse—laden with uncertainty, debate, and enthusiasm. Even as a student, I could participate in a collective understanding of an invisible illness. There was a palpable sense of connection as we navigated an unfamiliar path of accelerated discovery together. It is delicately exciting to be at the brink of discovery. But with highs come deep lows, and for the first time, I understood how effortful it is build the knowledge and evidence necessary to rigorously support a single sentence in a medical textbook. The entire profession of medicine—physicians and trainees alike—watched, rapt, as vaccines for an enigmatic virus were trialed and failed. As pharmacology of cures was embraced and disputed. As public health efforts steered in dizzying directions. As neglected social inequities and their suffocating hold on public health were magnified. While all this unfolded, the same detailed medical knowledge that once seemed onerous to me became a new foundation for evolving clinical practice. I spent my medical school years trudging through clinical knowledge, feeling troubled by its magnitude yet hoping that studying it all might be enough one day. Lifelong learning, of course, seemed necessary but felt like a remote habit that might be relevant years after graduation. A pandemic nudges change. For me, this pandemic helped inspire newfound gratitude for the arduous nature of discovery, the privilege of collective scholarship, and the necessity of humble perspective in meaningful learning. Acknowledgments: The author would like to thank her mentor Donald Redelmeier for continuing to inspire curiosity, optimism, and integrity as a learner.
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 | 0,036 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,006 | 0,005 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,016 | 0,025 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 0,005 |
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 ».