Teaching and Researching Ethically: Guidance for Instructor-Researchers, Educational Developers, and Research Ethics Personnel
Bibliographic record
Abstract
Despite now long-standing recognition of the value and importance of the scholarship of teaching and learning, questions continue to be raised about how to satisfy the hybrid responsibilities of teaching and research. The key message of this paper is that instructor-researchers, educational developers, and research ethics personnel should consider two key guidance documents in tandem: the Society for Teaching and Learning in Higher Education’s statement on Ethical Principles in University Teaching (Murray, Gillese, Lennon, Mercer, & Robinson, 1996) and the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans (Canadian Institutes of Health Research, Natural Sciences and Engineering Research Council of Canada, & Social Sciences and Humanities Research Council of Canada, 2014). Together these documents provide much needed guidance for teaching and researching ethically. Bien que la valeur et l’importance de l’avancement des connaissances en enseignement et en apprentissage soient reconnues depuis longtemps, on continue à se poser des questions pour savoir comment satisfaire les doubles responsabilités d’enseignement et de recherche. Le message principal de cet article est que les instructeurs-chercheurs, les conseillers pédagogiques et le personnel d’éthique de la recherche devraient prendre en considération deux documents principaux d’orientation en tandem : la déclaration de la Société pour l’avancement de la pédagogie dans l’enseignement supérieur sur les « Principes éthiques dans l’enseignement universitaire » (Ethical Principles in University Teaching - Murray, Gillese, Lennon, Mercer, & Robinson, 1996) et « Énoncé de politique des trois Conseils : Éthique de la recherche avec des êtres humains » (Conseil de recherches en sciences humaines du Canada, Conseil de recherches en sciences naturelles et en génie du Canada, & Instituts de recherche en santé du Canada, 2014). Ensemble, ces documents fournissent une orientation utile pour enseigner et mener des recherches de manière éthique.
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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 | 0.339 | 0.457 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.017 | 0.047 |
| Scholarly communication | 0.034 | 0.026 |
| Open science | 0.008 | 0.019 |
| Research integrity | 0.033 | 0.066 |
| Insufficient payload (model declined to judge) | 0.005 | 0.012 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".