68. The resident experience in a large urban teaching setting: Results of the 2005-2006 resident exit survey, University of Torontos
Bibliographic record
Abstract
We developed and implemented an annual online survey to administer to residents exiting residency training in order to (1) assess the quality of the residency experience and (2) identify areas of strength and areas requiring improvement. Long-term goals include program planning, policy-making and maintenance of quality control. Survey content was developed from an environmental scan, pre-existing survey instruments, examination of training criteria established by the CFPC and the CanMEDS criteria established by the RCPSC. The survey included evaluation benchmarks and satisfaction ratings of program director and faculty, preparation for certification and practice, quality of life, quality of education, and work environment. The response rate was 28%. Seventy-five percent of respondents were exiting from Royal College training programs. Results of descriptive statistics determined that the overall educational experience was rated highly, with 98.9% of respondents satisfied or very satisfied with their overall patient care experience. Ninety-six percent of respondents were satisfied or very satisfied with the overall quality of teaching. Preparation for practice was identified as needing improvement, with 26% and 34% of respondents giving an unsatisfactory rating to career guidance and assistance with finding employment, respectively. Although 80% of respondents reported receiving ongoing feedback and 84% discussed their evaluations with their supervisors, only 38% of evaluations were completed by the end of the rotation. The results indicate that residents are generally satisfied with their experiences during residency training, especially with their overall educational experience. Areas of improvement include preparation for practice and timeliness of evaluations. Further iterations of this survey are needed to refine the instrument, identify data trends and maintain quality control in residency training programs. Frank JR (ed.). The CanMEDS competency framework: better standards, better physicians, better care. Ottawa: The Royal College of Physicians and Surgeons of Canada, 2005. Merritt, Hawkins and Associates. Summary Report: 2003 Survey of final-year medical residents. http://www.merritthawkins.com/pdf/MHA2003residentsurv.pdf. Accessed May 1, 2006. Regnier K, Kopelow M, Lane D, Alden A. Accreditation for learning and change: Quality and improvement as the outcome. The Journal of Continuing Education in the Health Professions 2005; 25:174-182.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".