The Interplay Between the Abstract and the Particular: Research Ethics Standards and the Practice of Research as Symbolic
Bibliographic record
Abstract
Ethical standards for research with human participants are increasingly important. With respect to nursing research these standards are symbolic of the interplay between the abstract theoretical aspects of bioethical standards and the particulars of nursing practice. In this column, this interplay is symbolized as a reflective equilibrium. These standards are argued to symbolize not only the dialectic relationship between the abstract and the particular in ethics, but also the general lack of a nursing specific articulation of ethical standards. Further understanding of the distinctiveness of nurses' moral judgments and knowledge is presented as necessary in strengthening the reflective equilibrium.
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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 | 0.036 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.003 | 0.037 |
| Scholarly communication | 0.016 | 0.020 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.007 | 0.015 |
| 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; 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".