Farewell to humanism? Considerations for nursing philosophy and research in posthuman times
Bibliographic record
Abstract
In this paper, I argue that critical posthumanism is a crucial tool in nursing philosophy and scholarship. Posthumanism entails a reconsideration of what 'human' is and a rejection of the whole tradition founding Western life in the 2500 years of our civilization as narrated in founding texts and embodied in governments, economic formations and everyday life. Through an overview of historical periods, texts and philosophy movements, I problematize humanism, showing how it centres white, heterosexual, able-bodied Man at the top of a hierarchy of beings, and runs counter to many current aspirations in nursing and other disciplines: decolonization, antiracism, anti-sexism and Indigenous resurgence. In nursing, the term humanism is often used colloquially to mean kind and humane; yet philosophically, humanism denotes a Western philosophical tradition whose tenets underpin much of nursing scholarship. These underpinnings of Western humanism have increasingly become problematic, especially since the 1960s motivating nurse scholars to engage with antihumanist and, recently, posthumanist theory. However, even current antihumanist nursing arguments manifest deep embeddedness in humanistic methodologies. I show both the problematic underside of humanism and critical posthumanism's usefulness as a tool to fight injustice and examine the materiality of nursing practice. In doing so, I hope to persuade readers not to be afraid of understanding and employing this critical tool in nursing research and scholarship.
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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 | 0.028 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.012 | 0.132 |
| Scholarly communication | 0.016 | 0.027 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.009 | 0.016 |
| Insufficient payload (model declined to judge) | 0.007 | 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".