Relying on Others’ Reliability: Challenges in Clinical Teaching Assessment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The quality of the data generated from internally created faculty teaching instruments often draws skepticism. Strategies aimed at improving the reliability and validity of faculty teaching assessments tend to revolve around literature searches for a replacement instrument(s). PURPOSE: The purpose was to test this "search-and-apply" method and discuss our experiences with it within the context of observational assessment practice. METHOD: In a naturalistic pilot test, two previously validated faculty assessment instruments were paired with a global question. The reliability of both metrics was estimated. RESULTS: Generalizability analyses indicated that for both pilot tested faculty teaching instruments, the global question was a more reliable measure of perceived clinical teaching effectiveness than a multiple-item inventory. Item analysis with Cronbach's coefficient alpha suggested redundant instrument content. Rater error accounted for the greatest proportion of the variance and straight-line responses occurred in approximately 28% of residents' appraisals. CONCLUSIONS: The results of the present study draw attention to one of the common fallacies surrounding instrument-based assessment in medical education; the solution to improving one's assessment practice primarily involves identifying a previously published instrument from the literature. Academic centers need to invest in ongoing quality control efforts including the pilot testing of any proposed instruments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.007 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it