[Rally-resources. The integration of community principles].
Bibliographic record
Abstract
PROBLEM BEING ADDRESSED: Family medicine training programs are required to teach the four principles of family medicine, two of which deal with community responsibilities. Teachers in the Family Practice Unit at the Centre hospitalier de Québec, pavillon St-François d'Assise (UMF-SFA) have developed a learning activity that introduces residents to community agencies in the area. OBJECTIVE OF PROGRAM: To introduce family medicine residents to community aspects of the principles of family medicine, to help them identify community resources in the area served by UMF-SFA, to discuss these services so that they can use them effectively, and to offer new residents an opportunity to become better acquainted with these services and with the UMF-SFA team. MAIN COMPONENTS OF PROGRAM: In early September, a half-day is set aside for a rally during which mixed teams of supervisors and residents (four to eight to a team) visit about 10 community agencies in the vicinity of UMF-SFA. Walking from place to place, the teams spend 15 to 20 minutes with staff or users of each agency. The informal tone of the rally makes it easier for residents to understand these agencies. CONCLUSION: Each year for the past 10 years, all UMF-SFA members have taken part in a rally that introduces residents to the community-based resources of family medicine.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.186 | 0.070 |
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".