Methodological and theoretical contributions of critical discourse analysis to nursing research
Bibliographic record
Abstract
Critical discourse analysis is a methodological approach that allows for the questioning of structures that relegate certain ideas and certain people to the margins. In health sciences, this approach, with its origins in the field of critical linguistics, is useful for highlighting the many societal processes that privilege certain conceptions of health and health care while labelling other perspectives as « alternative" or "fringe". However, critical discourse analysis is still underused in nursing science despite its emancipatory potential. We attribute this reluctance, among other things, to its theoretical anchoring, to its linguistic origin, and to the vagueness and variability of its analysis methods. The objective of this article is therefore to better understand how critical discourse analysis can be used in the discipline of nursing to shed light on the power dynamics and social inequalities that persist. Different examples of studies carried out using critical discourse analysis are also presented to concretely illustrate how this approach can be used in nursing sciences.
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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 | 0.086 | 0.119 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.018 | 0.013 |
| Science and technology studies | 0.011 | 0.067 |
| Scholarly communication | 0.022 | 0.018 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.007 | 0.006 |
| 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".