Myth or Reality: Self-Assessment Is Central to Effective Curriculum in Anatomical Pathology Graduate Medical Education
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
Self-assessment, a personal evaluation of one's professional attributes and abilities against a perceived norm, has frequently been cited as a necessary component of self-directed learning and the maintenance of competency within regulated health professions, including the medical professions. However, education research literature has consistently shown uninformed personal global assessment of performance to be inaccurate in a variety of contexts, and have limited value in a workplace-based curriculum. Incorporating known standards of performance with internal and external data on the performance improves a learner's ability to accurately self-assess. Selecting content suitable for self-assessment, providing explicit assessment standards, encouraging feedback-seeking behaviors, supporting a growth mindset, and providing quality feedback in a supportive context are all strategies that can support learner self-assessment, learner engagement in reflection, and action on feedback in Anatomical Pathology graduate medical education.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.006 |
| 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