Advancing the Clinician Educator Career Pathway in Oncology
Bibliographic record
Abstract
PURPOSE: Education is an important component of cancer care; however, most clinician educators (CEs) receive little formal training in this area. Little is known about the factors that influence oncologists to pursue a career as a CE. The primary objective of this study was to determine the current state of oncologists' perceptions regarding the clinician educator role. MATERIALS AND METHODS: A one-time cross-sectional survey was administered to program directors/associate program directors (PDs/APDs) and fellows in November 2021. The survey was meant to elicit their perceptions regarding the CE role, training opportunities, and barriers to a career as a CE. RESULTS: The surveys were completed by a total of 2,134 oncology fellows and 88 PDs/APDs. Most PDs/APDs were female (52%), were associate professors (42%), and considered themselves a CE (82%). Over one-third of PDs/APDs reported no formal educator training (67%) and did not have a CE track for fellows at their institution (76%). The majority of PDs/APDs (80%) perceived the CE track to be a viable career pathway. Over half of fellows (56%) perceived the CE track to be a viable career pathway. Approximately one-third (62%) reported receiving CE training during their residency/fellowship. The top reported barriers to a career in medical education were a lack of jobs and opportunity for future promotions. CONCLUSION: Oncology PDs/APDs and fellows perceive the CE to be a viable career track. Greater advocacy efforts are needed to raise awareness about this career path.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".