Civilizing the ‘Barbarian’: a critical analysis of behaviour modification programmes in forensic psychiatry settings
Bibliographic record
Abstract
AIM: Drawing on the works of Erving Goffman and Michel Foucault, this article presents part of the results of a qualitative study conducted in a forensic psychiatry setting. BACKGROUND: For many years, behaviour modification programmes (BMPs) have been subjected to scrutiny and harsh criticism on the part of researchers, clinicians and professional organizations. Nevertheless, BMPs continue to be in vogue in some 'total' institutions, such as psychiatric hospitals and prisons. METHOD: Discourse analysis of mute evidence available in situ was used to critically look at behaviour modification programmes. RESULTS: Compelling examples of behaviour modification care plans are used to illustrate our critical analysis and to support our claim that BMPs violate both scientific and ethical norms in the name of doing 'what is best' for the patients. CONCLUSION: We argue that the continued use of BMPs is not only flawed from a scientific perspective, but constitutes an unethical approach to the management of nursing care for mentally ill offenders. IMPLICATIONS FOR NURSING MANAGEMENT: Nurse managers need to be aware that BMPs violate ethical standards in nursing. As a consequence, they should overtly question the use of these approaches in psychiatric nursing.
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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 | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".