An Examination of the Appropriateness of Using a Common Peer Assessment Instrument to Assess Physician Skills across Specialties
Bibliographic record
Abstract
PROBLEM STATEMENT: To determine whether a common peer assessment instrument can assess competencies across internal medicine, pediatrics, and psychiatry specialties. METHOD: A common 36 item peer survey assessed psychiatry (n = 101), pediatrics (n = 100), and internal medicine (n = 103) specialists. Cronbach's alpha and generalizability analysis were used to assess reliability and factor analysis to address validity. RESULTS: A total of 2,306 (94.8% response rate) surveys were analyzed. The Cronbach's alpha coefficient was.98. The generalizabililty coefficient (mean of 7.6 raters) produced an Ep(2) =.83. Four factors emerged with a similar pattern of relative importance for pediatricians and internal medicine specialists whose first factor was patient management. Communication was the first factor for psychiatrists. CONCLUSIONS: Reliability and generalizability coefficient data suggest that using the instrument across specialties is appropriate, and differences in factors confirm the instrument's ability to discriminate for specialty differences providing evidence of validity.
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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 | 0.078 | 0.331 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".