Bibliographic record
Abstract
BACKGROUND: Clinical teaching competency is a professional necessity ensuring that clinicians' knowledge, skills and attitudes are effectively transmitted from experts to novices. The aim of this paper is to consider how clinical skills are transmitted from a historical and reflective perspective and to link these ideas with student and teacher perceptions of competence in clinical teaching. METHODS: The reflections are informed by a Delphi process and professional development survey designed to capture students' and clinicians' ideas about the attributes of a competent clinical teacher. In addition, the survey process obtained information on the importance and 'teachability' of these characteristics. RESULTS: Four key characteristics of the competent teacher emerged from the Delphi process: clinically competent, efficient organizer, group communicator and person-centred. In a subsequent survey, students were found to be more optimistic about the 'teachability' of these characteristics than clinicians and scored the attribute of person-centredness higher than clinicians. Clinicians, on the other hand, ascribed higher levels of importance to clinical competency, efficient organization and group communication than students. CONCLUSIONS: The Delphi process created a non-threatening system for gathering student and clinician expectations of teachers and created a foundation for developing methods for evaluating clinical competency. This provided insights into differences between teachers' and students' expectations, their importance, and professional development.
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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 | 0.016 | 0.076 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".