Doing <scp>F</scp>oucault: inquiring into nursing knowledge with <scp>F</scp>oucauldian discourse analysis
Bibliographic record
Abstract
Foucauldian discourse analysis (FDA) is a methodology that is well suited to inquiring into nursing knowledge and its organization. It is a critical analytic approach derived from Foucault's histories of science, madness, medicine, incarceration and sexuality, all of which serve to exteriorize or make visible the 'positive unconscious of knowledge' penetrating bodies and minds. Foucauldian discourse analysis (FDA) holds the potential to reveal who we are today as nurses and as a profession of nursing by facilitating our ability to identify and trace the effects of the discourses that determine the conditions of possibility for nursing practice that are continuously shaping and (re)shaping the knowledge of nursing and the profession of nursing as we know it. In making visible the chain of knowledge that orders the spaces nurses occupy, no less than their subjectivities, FDA is a powerful methodology for inquiring into nursing knowledge based on its provocation of deep critical reflection on the normalizing power of discourse.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.012 | 0.028 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| 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".