A conceptual framework of student professionalization for health professional education and research
Bibliographic record
Abstract
OBJECTIVES: To present a conceptual framework of student professionalization for health professional education and research. METHODS: Synthesis and discussion of a program of research on competency-based education. RESULTS: Competency-based education relies on active, situation-based group learning strategies to prepare students to become health professionals who are connected to patient and population needs. Professionalization is understood as a dynamic process of imagining, becoming, and being a member of a health profession. It rests on the evolution of three interrelated dimensions: professional competencies, professional culture, and professional identity. Professionalization occurs throughout students' encounters with meaningful learning experiences that involve three core components: the roles students experience in situations bounded within specific contexts. Educational practices conducive to professionalization include active learning, reflection, and feedback. CONCLUSIONS: This conceptual framework drives a research agenda aimed at understanding how students become health professional and how learning experiences involving action, reflection, and feedback foster that process and the advancement of professional practices.
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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 | 0.030 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.029 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".