Bibliographic record
Abstract
Nursing scholars have a long tradition of philosophizing. In a recent nursing philosophy seminar, I discussed the contribution of what I consider to be the Top nurse philosophers and how they have influenced nursing thought and action. I selected these 10 leading philosophers on the basis of the breadth of their influence and the significance of their contribution. While the individuals I selected may not have viewed their own work as philosophical in nature, I applied this term because their work considers the nature of nursing using methods of reason and argument (the tools of philosophy). I must admit that I was hard pressed to limit my list to 10. The list included philosophers with whom I do not necessarily agree but whose works have significantly shifted or furthered our understanding of nursing qua nursing. My list is somewhat chronological in order and, not surprisingly, is topped by Florence Nightingale, whose works on the nature of nursing served to shape the profession and discipline well into the 20th century. My second selection is the duo of Lavinia Dock and Isabel Maitland Stewart, for their work on the development of nursing and their writing about the need for nursing to be guided by principles rather than trial and error. I include Hildegard Peplau for her groundbreaking work on the interpersonal aspect of nursing. Peplau was one of the first theorists to articulate the importance of the relationship between the nurse and the patient.
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 | 0.010 | 0.049 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.014 | 0.019 |
| Insufficient payload (model declined to judge) | 0.013 | 0.009 |
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".