Review of Professional Ethics and Law in Education: A Canadian Guidebook
Bibliographic record
Abstract
It’s no secret that professional ethics is an imperative in teacher education whilst also being rarely dedicated a full course of study in either undergraduate or postgraduate programs (Maxwell et al., 2016). Sometimes teacher educators consider professional ethics and the law nearly interchangeable, assuming that what is legal is ethical and that following school policies will fill the obvious gaps; or that perhaps knowledge of the relevant code of ethics alongside teacher professional standards provides the parameters for good teacher judgement. On the other hand are theoretical approaches to applied ethics, assumed to provide transferable applications which transform teachers’ ethical character and inoculate them from unethical behaviour. Fortunately, Bruce Maxwell, Dianne Gereluk, and Christopher Martin are all too aware of the limits and challenges of these approaches and offer an excellent solution for even the most thoughtful teacher educators in professional and educational ethics, based in their collective, and considerable, contributions to the field in Canada and worldwide. Maxwell is known for his contributions to educational ethics, having authored in moral psychology, moral emotions, philosophy of education, and ethics education, as well as empirical and theoretical works focusing on the professions and teacher education particularly (Maxwell & Hirsch, 2020; Maxwell & Schwimmer, 2016; Forster & Maxwell, 2022). Gereluk is a political philosopher and policy analyst whose contributions to theory and practice in the field have addressed educational inequities, citizenship, radicalization, and human rights (Gereluk, 2012; Gereluk, 2023), as well as mentoring and teacher education in rural settings (Corbett & Gereluk, 2020). Martin’s work has contributed significantly to philosophy of education and addresses questions in educational aims of higher education, issues of indoctrination, ethics, justice, and education for democracy (Cuypers & Martin, 2011; Martin, 2022; Martin, 2023).
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.029 | 0.035 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.029 | 0.013 |
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".