Ethics Theories and Codes
Bibliographic record
Abstract
In 1949, the Boulder Conference tried to define psychotherapy in a way that it could be used to train clinical and counseling psychologists. Carl Rogers, president of the American Psychological Association in 1947, appointed David Shakow to chair a committee on defining and teaching psychotherapy. The difficulty reaching agreement on a definition of therapy is echoed in the difficulty agreeing on a basic theory of ethics. This chapter briefly reviews the theories of ethics to illustrate the vast diversity of ethics theories, which can be viewed as a strength. Utilitarianism focuses on results, consequences. Kantian ethics focuses on will and intention. While ethics is an inextricable part of feminism, multiculturalism is an inextricable part of feminist ethics. To create an ethics code, Canadian Psychological Association began with a critical analysis of the international and interdisciplinary literature to determine the primary purposes of codes of ethics and their perceived strengths and weaknesses.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.011 | 0.096 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".