Validity theory applied to entrustment as an approach to 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
In adopting entrustment-based assessments, the construct has shifted from assessing learners’ capability to provide competent care to their readiness for the responsibility for the welfare of patients and permission to perform clinical care with appropriate autonomy. Competence committees charged with making entrustment-based decisions must make decisions that are valid, fit for purpose, and interpreted appropriately. However, entrustment as a construct is complex and warrants a discussion regarding its relation to validity. While many different validity questions may be asked in the context of entrustable professional activities (EPAs), this chapter focuses on what we believe is the most salient and novel feature of EPA-based programs, which is the introduction of entrustment decision-making as an approach to assessment of health professionals in training. Validity theory, with reference to the models of Messick and Kane, is discussed in the context of entrustment. This leads to reflections on how some assumptions regarding validity may need to be reconceptualized, how sources of evidence and validity arguments can support defensible decisions, and how threats to validity must be considered and minimized.
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 | 0.004 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it