Person-oriented research ethics: integrating relational and everyday ethics in research
Bibliographic record
Abstract
Research ethics is often understood by researchers primarily through the regulatory framework reflected in the research ethics review process. This regulatory understanding does not encompass the range of ethical considerations in research, notably those associated with the relational and everyday aspects of human subject research. In order to support researchers in their effort to adopt a broader lens, this article presents a "person-oriented research ethics" approach. Five practical guideposts of person-oriented research ethics are identified, as follows: (1) respect for holistic personhood; (2) acknowledgement of lived world; (3) individualization; (4) focus on researcher-participant relationships; and (5) empowerment in decision-making. These guideposts are defined and illustrated with respect to different aspects of the research process (e.g., research design, recruitment, data collection). The person-oriented research ethics approach provides a toolkit to individual researchers, research groups, and research institutions in both biomedical and social science research wishing to expand their commitment to ethics in research.
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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 | 0.292 | 0.183 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.009 | 0.094 |
| Scholarly communication | 0.027 | 0.029 |
| Open science | 0.003 | 0.022 |
| Research integrity | 0.010 | 0.016 |
| Insufficient payload (model declined to judge) | 0.002 | 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".