Initial Residency Match Intentions of PGY3 Family Medicine-Emergency Medicine Enhanced Skills Program Applicants
Bibliographic record
Abstract
Context: Entry to enhanced skills training programs in Canada occurs following completion of core Family Medicine residency training. This study is designed to evaluate if these residents had alternate interests for specialty choice aside from family medicine at the time of initial application to first year residency training. The emergency medicine program is used due to the availability of centralized data for applicants. Objective: To understand the initial PGY 1 residency match intentions of Family Medicine residents who later apply to enhanced skills training in Emergency Medicine. Study Design and Dataset: A retrospective analysis using data from the Canadian Residency Matching Service (CaRMS) to analyze the original first choice discipline at the time of PGY 1 match for family medicine residents who are applicants to enhanced skills training in emergency medicine. This study was approved by the University of Calgary Conjoint Health Research Ethics Board. Population Studied: Applicants to enhanced skills training in emergency medicine in Canada between 2016 and 2020. Results: There is an increased proportion of residents who apply to enhanced skills training in Emergency Medicine that had a nonfamily medicine first choice discipline in their initial residency match relative to the overall cohort of family medicine residents. There is a higher proportion of male applicants and Canadian Medical Graduate applicants to the enhanced skills training program in Emergency Medicine relative to the overall cohort of family medicine residents. Conclusions: Enhanced skills training in Emergency Medicine in Canadian family medicine training programs draws an applicant pool more likely to have had a non-family medicine first choice discipline in the original first year residency match. This is an important consideration from a residency selection and training point of view and from a health human resources perspective as we consider numbers of family medicine trainees across the country in the context of what their future practice patterns will ultimately be.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".