Bibliographic record
Abstract
CONTEXT: The study of expertise in medical education has a long history of success. Researchers have identified and elaborated on many dimensions of expert performance. In part, this success has derived from researchers' ability to effectively isolate the dimensions and explore each separately. Although this deconstruction of the expert has been successful, the need to recombine the dimensions of expertise as part of an integrated construct of expert practice has recently become an increasingly evident imperative in health professions education. METHODS: The aims of this paper are first to explore dimensions of expert practice as they are expressed in the expertise literature; secondly, to describe more recent programmes of research that have tried to elaborate on how experts integrate these various dimensions during daily practice, and, finally, to examine the potential implications of research exploring how experts integrate their own knowledge and skills with the affordances of the environment in which they work. RESULTS AND CONCLUSIONS: There are both challenges and opportunities in elaborating an integrated discourse on expertise. Exploring directions for research related to this integrated construction of the practising expert may add an important dimension to our educational repertoire.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.006 | 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".