THE ROLE OF DIALOGUE IN DEFINING ETHICAL PRINCIPLES: THE CANADIAN CODE OF ETHICS FOR PSYCHOLOGISTS
Bibliographic record
Abstract
Psychologists' codes of ethics are constructed in dialogue. Through responsive and deliberative dialogues, concerns and aspirations have been articulated into the ethical principles and standards that psychologists adopt for their professional self-regulation. This article traces how such dialogues featured in developing the earliest, through to the present, Canadian Code of Ethics for Psychologists. The history of these dialogues shows psychologists responding to emerging concerns with ethical standards, and sometimes revisions to them, relevant to their practice. The experiences of two participants at the center of these dialogues are recounted, as are their present efforts to extend discussions of ethical principles into the international arena. Constructivist psychologists are encouraged to join the ongoing dialogues on ethics that shape their practice.
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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 | 0.047 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.043 | 0.107 |
| Scholarly communication | 0.025 | 0.008 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".