Oncology Education in Canadian Undergraduate and Postgraduate Medical Programs: A Survey of Educators and Learners
Bibliographic record
Abstract
BACKGROUND: The oncology education framework currently in use in Canadian medical training programs is unknown, and the needs of learners have not been fully assessed to determine whether they are adequately prepared to manage patients with cancer. METHODS: To assess the oncology education framework currently in use at Canadian medical schools and residency training programs for family (fm) and internal medicine (im), and to evaluate opinions about the content and utility of standard oncology education objectives, a Web survey was designed and sent to educators and learners. The survey recipients included undergraduate medical education curriculum committee members (umeccms), directors of fm and im programs, oncologists, medical students, and fm and im residents. RESULTS: Survey responses were received from 677 educators and learners. Oncology education was felt to be inadequate in their respective programs by 58% of umeccms, 57% of fm program directors, and 50% of im program directors. For learners, oncology education was thought to be inadequate by 67% of medical students, 86% of fm residents, and 63% of im residents. When comparing teaching of medical subspecialty-related diseases, all groups agreed that their trainees were least prepared to manage patients with cancer. A standard set of oncology objectives was thought to be possibly or definitely useful for undergraduate learners by 59% of respondents overall and by 61% of postgraduate learners. CONCLUSIONS: Oncology education in Canadian undergraduate and postgraduate fm and im training programs are currently thought to be inadequate by a majority of educators and learners. Developing a standard set of oncology objectives might address the needs of learners.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".