Devenir médecin généraliste : Et le bonheur, dans tout cela?
Bibliographic record
Abstract
Deux récents articles attirent l’attention sur la désaffection croissante frappant la médecine\ngénérale au terme des études de médecine. Ce constat amer n’est guère isolé et une série de publications récentes soulignent la même tendance au Canada, dans le monde anglo-saxon ou dans divers pays de la\ncommunauté européenne. Les causes de cet abandon progressif et les incitants mis en place avec des succès\ndivers ont été suffisamment évoqués pour que nous n’y revenions pas. Cette lente érosion est-elle inéluctable? Nous ne le pensons pas, ayant partagé longuement les craintes, espoirs et enthousiasmes de bon nombre d’étudiants en médecine et ébauché avec eux une pédagogie innovante d’enseignement de la médecine de première ligne. Puisse notre modeste contribution apporter une touche de sérénité à un débat qui en a bien besoin
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.026 | 0.008 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".