Ethics of psychological research: New policies; continuing issues; new concerns.
Bibliographic record
Abstract
The implementation over the past year within Canadian universities of the new Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans (TCPS) ushers in a new era in the oversight of the ethics of psychological research in Canada. Although these new policies apply to all human research, our interest in how they apply to psychology, primarily to deception, undergraduate subject pools, and other continuing concerns. Why have the granting agencies decided that government regulation of research ethics is necessary and what is the relationship between federal regulations and discipline codes? The history of CPA's involvement in protecting psychology's interests in the final revisions to the TCPS is recounted. In spite of what has been achieved, many psychologists feel that the TCPS has created new concerns for the discipline. Although there is the potential for startup problems, it is in our collective and individual best interests to make the policy work, thereby ensuring that escalation of government regulation or legislation will not be pursued.
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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 | 0.175 | 0.227 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.018 | 0.123 |
| Scholarly communication | 0.041 | 0.027 |
| Open science | 0.007 | 0.012 |
| Research integrity | 0.057 | 0.074 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".