The Script Concordance Test: A Tool to Assess the Reflective Clinician
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 Script Concordance (SC) test is a new assessment tool. It is designed to probe whether knowledge of examinees is efficiently organized for clinical actions. That kind of organization of knowledge is named a script. The SC test places examinees in written, but authentic, clinical situations in which they must interpret data to make decisions. PURPOSE: The SC test is designed to measure the degree of concordance that exists between examinees' scripts and scripts of a panel of experts. The objective of this article is to provide interested educators with the practical "how to" information needed to build and use an SC test. METHODS: The theoretical background of the SC test is described. The principles of construction of an SC test are presented, including the writing of clinical cases, the choice of item format, the validation of the test, and the elaboration of the scoring system. RESULTS: A series of studies have shown that the SC test has interesting psychometric properties, in terms of reliability, face validity, and construct validity. Results from these studies are succinctly presented and commented. CONCLUSION: The SC test is a simple and direct approach to testing organization and use of knowledge. It has the strong advantage for a testing method of being relatively easy to construct and use and to be machine-scorable. It can be either paper- or computer-based and can be used in undergraduate, postgraduate, or continuing medical education.
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 | 0.007 | 0.211 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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