Bibliographic record
Abstract
Notwithstanding the remarkable achievements made by medical science over the last half of the twentieth century, there is a palpable sense that a strictly medical view of human health, that is one founded on modernist assumptions, has become problematic, if not counterproductive. In this study, I argue that as nursing continues to eagerly welcome and indeed champion medical epistemology in the form of knowledge transfer, evidence-based practice, research utilization, outcomes-based practice, quantifiable efficiency and effectiveness, it risks becoming little more than a medical science addendum and indeed one that inherits the problems now facing contemporary medicine. The purpose of this study then is to attempt to resituate nursing as a discipline at work within an ontopolitical matrix of radical democratic pluralism. I begin by tracing a philosophical line from Kuhn's paradigms to Bloor's strong programme of Sociology of Scientific Knowledge. Following this, I attempt to explicate the thought of Bruno Latour as a philosophical alternative to Sociology of Scientific Knowledge. Next, I outline the radical pluralism of William Connolly in an effort to demonstrate its similarity to Latour's philosophy and finally how such a position is germane to contemporary nursing and the reality of politics. I do this with reference to the controversial issue of illicit drug use and harm reduction. In effect, I argue that such an issue cannot be dealt with using scientific evidence alone, but rather requires a philosophy of advocacy, what I term democratic advocacy, that is capable of responding to the politics of suffering, which is to say suffering that results from identity/difference.
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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.074 |
| Scholarly communication | 0.020 | 0.016 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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".