Resident Evaluation of Clinical Teachers Based on Teachers' Certification
Bibliographic record
Abstract
OBJECTIVE: To examine the influence of emergency medicine (EM) certification of clinical teaching faculty on evaluations provided by residents. METHODS: A prospective cohort analysis was conducted of assessments between July 1994 and July 2000 on residents' evaluations of EM faculty at the University of Alberta, Edmonton, Canada. Resident- and faculty-related variables were entered anonymously using the validated evaluation tool (ER Scale). Credentialing and demographic information on EM faculty was supplemented by data obtained through a nine-question survey. Groups were compared using ANOVA. RESULTS: The 562 residents returned 705 (91%) valid evaluation sheets on 115 EM faculty members. The four domains of didactic teaching, clinical teaching, approachability, and helpfulness were assessed. The majority of ratings were in the very good or superb categories for each domain. Instructors with certification in EM had higher scores in didactic, clinical teaching compared with others, and teachers without national certification scored lower in the helpful and approachable categories (p < 0.05). The route of obtaining EM certifications either through training or practice eligibility did not affect scores. Instructors under the age of 40 years had higher scores than the older age groups in three of four categories (p < 0.05). Instructors working at the teaching sites on a half-time basis received higher scores than those working full-time, and scores varied based on site. Overall, teaching ratings improved over the study period (p < 0.05). CONCLUSIONS: Significant differences exist among instructors in the EM setting that affect their teaching rating scores. National certification in EM, academic track, rotation year, and site are all correlated with better teaching performance.
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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 | 0.004 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".