From Subjective Opinion to Medical Fact: A Critical Discourse Analysis of Mental Health Nursing Education
Bibliographic record
Abstract
Using various methods and strategies of Critical Discourse Analysis, this article demonstrates how certain influential nursing texts generate a certain biomedical framing of the mental health nursing assessment. Accordingly, the mental health assessment in undergraduate nursing education becomes imbricated in processes of governance that legitimate psychiatric discourse by 1. Presenting the opinions and judgements of mental health professionals as objective scientific facts; 2. Utilizing grammatical mood and modality to convey a matter-of-fact urgency and necessity for psychiatric intervention that is made to appear largely through conjecture and passive logical leaps; and 3. Through hybrid fusion with other scientific and medical disciplines that lend credibility to psychiatry through association. While we largely focus on critique of the mental health assessment, we buttress this critique using two other institutional texts that draw on a psychiatric framing of mental health, to demonstrate how these texts reinforce and work in discursive cohesion with the mental health assessment. We conclude by discussing the implications of these consequences to nursing education and nursing students and educators alike.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 teacher head, 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".