Bibliographic record
Abstract
Across the professions (nursing, teaching, engineering, medicine, law, etc.) there is a call for early training to be taught in a way that is more relevant to practice in the field. National reports making recommendations on the future training of professionals emphasize the integration of classroom‐based knowledge with practice‐based knowledge. In medical education the call is for the basic medical sciences, which are typically taught by basic scientists in the university setting during the first two years of medical school, to be integrated with the context of clinical practice. The implementation of integration is presented as curricular change, with the assumption of relatively unproblematic collaboration between basic scientists and physicians to teach medicine in clinically relevant ways. One implication of such reform is that basic scientists, more than clinicians, will be required to change their former ways of knowing, teaching, and assessing performance in the basic sciences. This is not trivial, as it involves not only their sense of competency, but also their very identity as professionals and academics. Drawing from the literature on educational change, in the context of anatomy education, this presentation will introduce a conceptual framework that will help us better think about and investigate the experience of making such a shift in professional competence and identity for anatomists. Grant Funding Source : UBC Four Year Fellowship
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.030 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.011 | 0.015 |
| Scholarly communication | 0.024 | 0.025 |
| Open science | 0.003 | 0.022 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".