Psychologists' perceptions of ethically troubling incidents across international borders
Bibliographic record
Abstract
This article provided a brief history of the development of codes of ethics for psychologists and the desire for a universal code. It reviewed recent studies on ethical dilemmas reported by psychologists in nine primarily Western countries: United States, United Kingdom, Norway, Finland, Canada, Sweden, New Zealand, South Africa, and Mexico. The Pope and Vetter ( 1992) model was used to ask psychologists for an ethically troubling incident encountered over the previous year. The combined data of a total of 2698 responses revealed that issues of confidentiality followed by dual relationships were the most frequent. There was considerable agreement on the nature of ethical dilemmas in the countries represented. There are limitations in reviewing studies based on reports in the public arena without access to the original data. Sample sizes were small and it is not known to what extent there was a lack of standardization in the methodology and analysis of responses. However, these studies were of practical value in (a) addressing issues within each country (e.g., revising codes of ethics, identifying needs for education in ethics, and identifying the need for more specific guidelines), (b) indicating similarities across reporting countries, and (c) noting that country‐specific differences appear to relate more to working conditions and nature of clientele than to differences in cultural values and beliefs. The relevance for initiatives to develop a universal declaration of ethical principles for psychologists is limited by the absence of representation from non‐Western and aboriginal cultures.
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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 | 0.030 | 0.089 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.014 | 0.014 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 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".