Ranking in Canadian Gastroenterology Residency Match: What Do Residents and Program Directors Want?
Bibliographic record
Abstract
BACKGROUND: Matching to a gastroenterology (GI) fellowship position in Canada is increasingly competitive. OBJECTIVE: To identify factors that determine how residents rank programs across the country, and how program directors rank their applicants. METHODS: Using input from several current GI trainees and former program directors, two separate surveys were developed. An online survey was sent one month after the match to every resident matched to an adult GI program in the 2007 match. A separate online survey was simultaneously sent to all program directors of 14 accredited GI programs in Canada. Two subsequent cohorts (2008 and 2009) of matched residents were surveyed during the annual GI fellow endoscopy course at McMaster University (Hamilton, Ontario). RESULTS: The overall response rate was 64 of 91 (70%) for residents and 11 of 15 (73%) for program directors (one program had codirectors). Using a five-point Likert scale for rating the importance of various factors influencing their decision, residents from three years ranked the following factor as most important: suitable location for spousepartnerfamily (median score = 5). The overall least important factor was an opportunity for pediatric elective (median score = 2). Using the same scale, program directors ranked the following factors as most important (median score = 5) in ranking residents to their program: the ability to get along with others, outstanding reference letters, exceptional curriculum vitae and applying to only one specialty. CONCLUSIONS: Several factors important for GI applicants and program directors were identified, as well as a few less-important factors. Based on these results, GI training programs can more effectively market their programs to applicants in the future, and residents applying to GI programs can strengthen their applications in the ever competitive match process.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".