Furthering the “Theory Debate” in the Scholarship of Teaching: A Proposal Based on MacIntyre’s Account of Practices
Bibliographic record
Abstract
Initiatives intended to support and advance the scholarship of teaching have become common in Canada as well as internationally. Nonetheless, the notion of a scholarship of teaching remains contested and has been described as under-theorized. In this conceptual study, I contribute to the ongoing “theory debate” in the scholarship of teaching, applying a philosophical lens. I propose that Alasdair MacIntyre’s account of “practices,” including concepts of virtue, standards of excellence, internal goods, and transformation, offers a useful theoretical framework by which to identify the nature and defend the purposes and desired outcomes of this domain of scholarship. I argue that the moral virtues of justice, courage, and truthfulness, identified by MacIntyre as fundamental to all social practices, are essential also for meaningful engagement in the practice of the scholarship of teaching, but that two additional and overarching virtues are needed: authenticity and phronesis.
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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 | 0.042 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.013 | 0.155 |
| Scholarly communication | 0.019 | 0.031 |
| Open science | 0.006 | 0.014 |
| Research integrity | 0.017 | 0.018 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".