Nursing Knowledge and Human Science Revisited: Practical and Political Considerations
Bibliographic record
Abstract
The human science tradition is rooted in human freedom and meaning and oriented toward narrative and dialogical methods. In the past 10 years, human science nursing has grown but the opposition has also increased. Whereas other health disciplines are turning to the study of lived experience, nursing on the whole may be turning away. This article updates progress in human science, including works related to major nursing theories. The authors address practical and political considerations related to language, community, theory-laden knowledge, and tolerance for diversity. The authors conclude that the suppression of human science imperils nursing as a practice of being-with, witnessing, and cocreating quality of life, lived by nurses. But theories live in the actions of those who support them; thus, any place where people seek human care has the potential to support a human science-based nursing practice.
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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 | 0.032 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.006 | 0.066 |
| Scholarly communication | 0.018 | 0.024 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.020 | 0.019 |
| 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".