Bibliographic record
Abstract
In 2002, 95.6% of medical students registered with the Canadian Resident Matching Service were assigned to a program during the match's first round. Among successful applicants, 62% were matched to the program they had ranked first, and 90% were matched to their first-ranked discipline. Students from McMaster and Memorial universities were most successful in the latter category (96% and 95% respectively), followed by those from the University of Western Ontario (93%), the University of Ottawa (92%) and the University of Calgary and Queen's University (91%). About two-thirds of Memorial and McGill graduates were matched to positions at those same schools. Elsewhere, many more students packed their suitcases: 21% moved to a residency position within the same province, while 36.4% left for a position in another province. Among all applicants, women were slightly more successful than men at being matched to their first choice of discipline (86.7% vs. 82.7%). More than one-third (34.4%) of women were matched to family medicine positions, while less than one-fifth of men (18.2%) will be taking that route into practice. Family medicine accounted for 38.8% of the 1260 available positions, but 109 of them remained unfilled after the first round; 62 were subsequently filled during the second iteration. Eighty-three residency positions were filled by international medical graduates, who could enter only the second iteration. Overall, 1 in 6 international applicants (16.7%) was matched successfully, with 47 family medicine positions being filled by these applicants. — Shelley Martin, Senior Analyst, CMA Research, Policy and Planning Directorate
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 | 0.006 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.105 | 0.036 |
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".