Ethical Dilemmas, Cultural Differences, and the Globalization of Psychology
Bibliographic record
Abstract
Abstract As the world becomes globalized, psychologists more frequently encounter ethical dilemmas based on differences in worldviews. Enlightened globalization may lead to greater harmony, while unilateral globalization by dominant cultures will not. This chapter presents practical examples for psychologists of culture-based ethical dilemmas around such themes as respect, competency, professional boundaries, the status of women, the law, and social justice. Today, psychologists and counselors may come from different cultures, train in different countries, and practice with a diversity of clients and in a diversity of locations. When cultural beliefs appear to clash with ethical rules of conduct, ethical decision making must focus on the well-being of clients individually and collectively. Respect and caring for clients takes priority over Western concepts of rule-compliance. The vignettes of ethical dilemmas illustrate some of the complexities of working across cultures. Psychologists are urged to support an enlightened globalization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".