General practitioner surgery: anyone interested?
Bibliographic record
Abstract
INTRODUCTION: We sought to assess awareness of, exposure to and interest in general practitioner (GP) surgery and enhanced surgical skills (ESS) among family practice residents in British Columbia, Alberta and Saskatchewan. METHODS: We distributed a survey to all family practice residents at 4 universities in BC, Alberta and Saskatchewan. The survey assessed demographic information, awareness of and exposure to GP surgery or ESS during training, and interest in pursuing formal ESS training. RESULTS: We received 174 responses (27.2% response rate). Numerous respondents were unaware of GP surgery (9.9% ± 4.5%) and ESS (17.9% ± 5.7%). Awareness was higher among respondents from rural hometowns (GP surgery and ESS awareness 100% and 94.1%, respectively), and with prior exposure to GP surgery (GP surgery and ESS awareness 96.9% and 95.4%, respectively). A minority (38.2%) had been exposed to GP surgery, with exposure higher in respondents from rural training sites and in their second postgraduate year (72.5% and 47.4%, respectively). A quarter (25.1%) of respondents were considering ESS training. Factors encouraging training included increased procedures, challenging medicine and impact on patient outcomes. The importance of ESS training opportunities and service was rated highly. CONCLUSION: Many respondents were unaware of ESS as a career option. Exposure to GP surgery during training was associated with increased awareness. Furthermore, exposure fostered interest in this important field. These results may be helpful in the development of formal ESS training programs and in curricula for family practice residency programs.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.054 | 0.010 |
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".