Bibliographic record
Abstract
BACKGROUND: This paper conceptualizes nursing as a health profession in transformation at the beginning of the 21st century. We frame our analysis using Michel Foucault's concept of governmentality. While extensively quoted and used in other disciplines, the work of the late French philosopher has been cited infrequently in the nursing literature. Yet a closer look at his work reveals how Foucault offers a relevant entry point for revisiting nursing theory and nursing practice. AIM OF THE PAPER: aim of this paper is to reflect on nursing practice as it is inscribed within the state's modus operandi. We discuss the prevalent notion that nurses are powerless and suggest they do exercise power in many ways and that they are a powerful group. RESULTS: In this paper we show how nursing is a means of governmentality of individuals and of the population because its practices contribute to the management of society through a vast range of power techniques. These techniques range from disciplining individuals to promoting discourses that construct desirable subjectivities. Within this perspective, the emergence of political aspects of nursing theory and nursing practice are made explicit. CONCLUSION: We explore the limits and potentials of the concept of governmentality to the understanding of nursing as a health profession. This concept can generate a form of critical immobilism, but also promotes a more politically complex understanding of nursing practice.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.025 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".