Beyond Individual Rights and Freedoms: Metaethics in Social Work Research
Bibliographic record
Abstract
Increasingly, social workers are called on to demonstrate the efficacy of their interventions and to contribute to knowledge building in the social sciences. Although social workers have a long tradition of practice ethics, less attention has been given to the unique dimensions of research ethics for social workers. A social work model of research ethics would consider how to balance highly valued ethical principles that are individually focused, such as self-determination and nonmalfeasance (the obligation to do no harm), with equally important values that have a collective focus, such as justice and beneficence (the obligation to bring about good). This article reviews current principles guiding research ethics, such as autonomy, beneficence, nonmalfeasance, and justice and provides an outline of the salient issues for social workers as they strive to address individual and collective interests in research endeavors, such as a greater emphasis on the social justice mission and the need to ensure that social justice objectives do not obscure individual rights and freedoms. The article concludes with preliminary recommendations for developing a social work perspective in research ethics.
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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 | 0.388 | 0.349 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.014 | 0.011 |
| Science and technology studies | 0.010 | 0.089 |
| Scholarly communication | 0.025 | 0.049 |
| Open science | 0.007 | 0.016 |
| Research integrity | 0.012 | 0.017 |
| 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".