Being Ethically Minded: Practising the Scholarship of Teaching and Learning in an Ethical Manner
Bibliographic record
Abstract
The authors propose a working definition of ethical Scholarship of Teaching and Learning (SoTL), advance an ethical framework for SoTL inquiry, and present a case study that illustrates the complexity of ethical issues in SoTL. The Ethical SoTL Matrix is a flexible framework designed to support SoTL practitioners, particularly in the formative stages of their inquiries. Three dominant ethical traditions form the basis of the matrix: teleological or pragmatic, external, and deontological. The key message of the paper is that SoTL practitioners should reflect on different perspectives in their efforts to do what is right in any given situation. The matrix introduces three dominant ethical traditions, but SoTL practitioners may ultimately move beyond these traditions to explore a range of ethical considerations appropriate to their projects and disciplines.
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 | 0.071 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.016 | 0.116 |
| Scholarly communication | 0.028 | 0.025 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.013 | 0.017 |
| Insufficient payload (model declined to judge) | 0.002 | 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".