Towards understanding the unpresentable in nursing: some nursing philosophical considerations
Bibliographic record
Abstract
While nursing practice embodies certain observable and sometimes habitual actions, much inheres in these actions that is not immediately discernible. Taking on Lyotard's exegesis of the unpresentable, I undertake an analysis of the unpresentable as it occurs in nursing practices. The unpresentable is a place of alterity often excluded from dominant discourses. Yet this very alterity is what practising nurses face day after day. Drawing from two nursing situations, one from a hermeneutic phenomenological study and the other from the literature, I elucidate the unpresentable from a nursing point of view. Evoking Lyotard as well as selected philosophers from the continental philosophical tradition, I also question whether nursing in its present discourse is capable of responding to the unpresentable in nursing situations. Through the philosophical stance of presentation and representation, I delineate the urgent need to bring the otherness of the unpresentable into our nursing discourse. Nurses in practice confront a wide array of human differences and diversities and come to the realization that no framework alone can ever really have primacy over the multiform presentations of human suffering that so strikingly evoke alterity.
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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 | 0.016 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.004 | 0.033 |
| Scholarly communication | 0.011 | 0.027 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.010 | 0.011 |
| 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".