Ambiguous Opportunity: Toiling for Truth of Nursing Art and Science
Bibliographic record
Abstract
This article questions traditional boundaries between nursing art and nursing science and explores how nurses build knowledge and truth. A brief overview of familiar notions about nursing art is followed by questions that are meant to deepen understanding about nursing and the knowledge required for a discipline. Authors describe understanding as an event that heralds human creation of meaning and potential action. Art is then shown to be a way to enhance understanding and meaningful knowledge when woven with nursing theory to guide practice. Findings from Parse's research method are described as artistic expressions, and borders that have served to separate notions about nursing art and science are challenged. The hermeneutics of human becoming are presented as beacons for truth and understanding. Authors call for tolerance of ambiguity and openness to support dialogue and discovery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.016 | 0.094 |
| Scholarly communication | 0.025 | 0.029 |
| Open science | 0.002 | 0.021 |
| Research integrity | 0.007 | 0.009 |
| 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".