Drug samples in family medicine teaching units: a cross-sectional descriptive study: Part 2: portrait of drug sample management in Quebec.
Bibliographic record
Abstract
OBJECTIVE: To draw a portrait of drug sample management in academic primary health care settings and assess conformity to existing Canadian guidelines. DESIGN: Descriptive cross-sectional survey. SETTING: All 33 family medicine teaching units (FMTUs) in Quebec that kept drug samples. PARTICIPANTS: ). MAIN OUTCOME MEASURES: (2007). RESULTS: All 33 FMTUs responded to the questionnaire. According to managers, no FMTUs had written selection criteria to guide sample choice. Almost one-third (30%) of FMTUs had uncontrolled access to drug sample cabinets. Even though pharmaceutical companies must distribute drug samples to authorized professionals only, these professionals were involved in the procurement and the reception of samples in 79% and 56% of FMTUs, respectively. Only 15% of FMTUs kept track of samples distributed, 82% checked expiration dates, and 85% ensured proper disposal as recommended. CONCLUSION: The management of drug samples in the FMTUs in Quebec is heterogeneous, with many FMTUs and pharmaceutical companies not following Canadian guidelines.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".