Canadian vascular surgery residents' perceptions regarding future job opportunities
Bibliographic record
Abstract
The objective was to determine the employment environment for graduates of Canadian vascular surgery training programs. A cross-sectional survey of residents and graduates (2011-2012) was used. Thirty-seven residents were invited with a response rate of 57%, and 14 graduates with a response rate of 71%; 70% of graduates felt the job market played an important role in their decision to pursue vascular surgery as a career compared to 43% of trainees. The top three concerns were the lack of surgeons retiring, the overproduction of trainees, and saturation of the job market. The majority (62%) of trainees see themselves extending their training due to lack of employment. All of the graduates obtained employment, with 50% during their second year (of two years) of training and 30% after training was completed. Graduates spent an average of 12 ± 10.6 months seeking a position and applied to 3.3 ± 1.5 positions, with a mean of 1.9 ± 1.3 interviews and 2 ± 1.2 offers. There was a discrepancy between the favorable employment climate experienced by graduates and the pessimistic outlook of trainees. We must be progressive in balancing the employment opportunities with the number of graduates. Number and timing of job offers is a possible future metric of the optimal number of residents.
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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 | 0.005 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".