Competency assessors’ cognitive map of practice when assessing practice based encounters
Bibliographic record
Abstract
Introduction: There is growing evidence that inconsistencies exist in how competencies are conceptualised and assessed. Aim: This study aimed to determine the reliability of pharmacist assessors when observing practice-based encounters and to compare and contrast assessors’ cognitive map of practice with the guiding competency framework. Methods: This was a qualitative study with verbal protocol analysis. A total of 25 assessors were recruited to score and verbalise their assessments for three videos depicting practice-based encounters. Verbalisations were coded according to the professional competency framework. Results: Protocols from 24 participants were included. Interrater reliability of scoring was excellent. Greater than 75% of assessment verbalisations were focused on 3 of the 27 competencies: communicate effectively, consults with the patient, and provide patient counselling. Conclusion: Findings support the notion that assessment completed within practice could be largely informed by a single component of the interaction or more specifically, what ‘catches the eye’ of the assessor.
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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 | 0.068 | 0.190 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".