Duoethnography as a dialogic and collaborative form of curriculum inquiry for resident professionalism and self-care education
Bibliographic record
Abstract
Medical residency is an important time in the development of physician professionalism, as residents' identities and medical responsibilities shift from student-learners to practitioner-leaders. During this transition time, many residents struggle with stress due to the unique pressures of their post-graduate training. This, in turn, can potentially hinder successful professional identity development. In response, the Royal College of Physicians and Surgeons of Canada (RCPSC) has incorporated physician health into its CanMEDS professional competency framework. Although this framework identifies enabling self-care professional competencies (e.g., capacity for self-regulation and resilience for sustainable practice), it does not specify the types of educational strategies best suited to teach and assess these competencies. To support the prevention and rehabilitation of resident health issues, residency training programs are faced with the complex challenge of developing socially accountable curricula that successfully foster self-care competencies. Duoethnography, a dialogic and collaborative form of curriculum inquiry, is presented as a pedagogical model for resident professionalism and self-care education. Merits of duoethnography centers on its: 1) capability to foster self-reflexive and transformative learning; 2) versatility to accommodate learner diversity; and 3) adaptability for use in different social, situational, and ethical contexts.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".