The effect of candidate familiarity on examiner OSCE scores
Bibliographic record
Abstract
CONTEXT: Although examiners are a large source of variability in the objective structured clinical examination (OSCE), the exact causes of examiner variance remain understudied. OBJECTIVE: This study aimed to determine whether examiner familiarity with candidates influences candidate scores. METHODS: A total of 24 candidates from 4 neonatal-perinatal training programmes participated in a 10-station OSCE. Sixteen trainees and 7 examiners came from a single centre (site A) and 8 candidates and 5 examiners came from the other 3 centres. Examiners completed station-specific binary checklists and an overall global rating; standardised patients (SPs) and standardised health professionals (SHPs) completed 4 process ratings and the overall rating. A fixed-effect, 2-way analysis of variance was performed to ascertain whether there was interaction between examiner site and candidate site. RESULTS: Interstation Cronbach's alpha was 0.80 for the examiner checklist, 0.88 for the examiner global rating and 0.88 for the SP or SHP global rating. Although the checklist scores awarded by site A examiners were significantly higher than those awarded by non-site A examiners, there was no significant interaction between examiner and candidate site (P = 0.124). Similarly, the interaction between examiner and candidate site for the global rating was not significant (P = 0.207). Global ratings awarded by SPs and SHPs were also higher in stations where site A faculty examined site A candidates, suggesting the observed differences may have been related to performance. CONCLUSIONS: Results from this small dataset suggest that examiner familiarity with candidates does not influence how examiners score candidates, confirming the objective nature of the OSCE. Confirmation with a larger study is required.
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.
How this classification was reachedexpand
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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".