Ethical Standards, Guidelines, and Related Issues Pertinent to International Testing and Assessment
Bibliographic record
Abstract
Chapter 29 focuses on the ethical conduct of psychologists in relation to assessment. The chapter starts by establishing the fact that at the international level, codes of ethics that relate to testing and assessment are rather the exception than the rule. A number of codes of ethics are, however, influential in this respect. These are discussed to some length in the chapter. First, three national codes are discussed: the Canadian Code of Ethics for Psychologists, the British Psychological Society Code of Ethical Conduct, and the APA Ethical Principles of Psychologists and Code of Conduct. Then the chapter focuses on two regional codes (the Meta-Code of the European Federation of Psychologists’ Associations and the Code of Ethical Principles of Nordic Psychologists) and on the general international code (the Universal Declaration of Ethical Principles for Psychologists). The chapter also discusses the Guidelines of the International Test Commission.
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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 | 0.019 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.021 | 0.011 |
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".