Team member expectations of trainee communicator and collaborator competencies – so shines a good deed in a weary world?
Bibliographic record
Abstract
BACKGROUND: Workplace-based assessment may be further optimized by drawing upon the perspectives of multiple assessors, including those outside the trainee's discipline. Interprofessional competencies like communication and collaboration are often considered suitable for team input. AIM: We sought to characterize multidisciplinary expectations of communicator and collaborator competency roles. METHODS: We adopted a constructivist grounded theory approach to explore perspectives of multidisciplinary team members on a clinical teaching unit. In semi-structured interviews, participants described expectations for competent collaboration and communication of trainees outside their own discipline. Data were analyzed to identify recurring themes, underlying concepts and their interactions using constant comparison. RESULTS: Three main underlying perspectives influenced interprofessional characterization of competent communication and collaboration: (1) general expectations of best practice; (2) specific expectations of supportive practice; and (3) perceived commitment to teaching practice. However, participants seemingly judged trainees outside their discipline according to how competencies were exercised to advance their own professional patient care decision-making, with minimal attention to the trainee's specific skillset demonstrated. CONCLUSION: While team members expressed commitment to supporting interprofessional competency development of trainees outside their discipline, service-oriented judgement of performance loomed large. The potential impact on the credibility of multidisciplinary sources for workplace-based assessment requires consideration.
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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 | 0.020 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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 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".