Discursive constructions of family functions in forensic psychiatry: A critical ethnographic perspective
Bibliographic record
Abstract
Significant barriers remain regarding the implementation of family-centred approaches in the domain of forensic psychiatry despite their effectiveness at increasing adherence to treatment, improving attendance to medical appointments, decreasing readmission rates and reducing episodes of relapse. We attribute these barriers to a fundamental gap in our understanding of the family function and its role within the forensic psychiatric system. Despite requesting to be included and considered as partners, some families feel excluded and sidelined, which causes distress, incomprehension and disengagement. We approached this tension at the discursive level through a critical ethnography of the Review Board and the work of Foucault on psychiatric power, which provided us with a unique opportunity to understand how the role of families are constructed and sustained in the Canadian forensic psychiatric system. To do so, we mobilized data stemming from ethnographic observations and documentary artifacts entitled 'reasons for disposition'. Data analysis allowed us to identify two discursive constructions of familial functions: (1) families as repositories of information and (2) families as supervisory agents. These results have implications for health care professionals and administrators in forensic psychiatry who are increasingly adhering to family-centred care models without questioning what such care or what such family engagement entails.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.030 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.024 | 0.067 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.004 |
| 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 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".