The Scholarship of Teaching in Health Science Schools
Bibliographic record
Abstract
Teaching is a core mission for all health science schools. Despite its key role in training new generations of health care professionals, teaching has been overshadowed by the revenue- and prestige-generating activities of research and clinical care. Research, both basic and clinical, is equated with scholarship and is rewarded in the promotion and tenure process, as well as with intramural and extramural funding. Clinical service generates revenue for schools; teaching, however, does not generate revenue, and, traditionally, teaching and the creative activity related to it have been seen not as scholarship but as an expectation. Over the last decade or so, scholars of teaching have called for a new view of scholarship that includes the scholarship of teaching. This view is broader in scope than scholarly teaching within a classroom or clinic. It refers to scholarly activity related to teaching that results in enduring products that are peer reviewed and broadly disseminated. These are examples of scholarly work and should be recognized as such. Academic institutions should value high-quality teaching and educational innovations and reward them as scholarly work. This article presents an overview of what the scholarship of teaching means, how it can be assessed, and the needed next steps.
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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 | 0.023 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.012 | 0.031 |
| Scholarly communication | 0.024 | 0.010 |
| Open science | 0.001 | 0.019 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".