Bibliographic record
Abstract
Community treatment orders (CTOs), which allow for involuntary psychiatric treatment of individuals who meet particular legal criteria while they are living in the community, have been in effect in Ontario since 2001. Some similar form of mandated community-based psychiatric treatment exists in every Canadian province and in many other jurisdictions around the world. In the wake of deinstitutionalization, CTOs filled a gap in mental health care, allowing for the treatment of people with serious and persistent mental illness (SPMI) who were otherwise unable or unwilling to access care; however, CTOs brought their own host of legal, ethical and practice dilemmas, as well as mixed results in research about their effectiveness. This doctoral research examines the way CTO policy is situated within a larger historical, social, legal and discursive system; the way it is deployed, operationalized and negotiated in day-to-day practice; and the layered effects that this has on the multiple actors involved. This study gives voice to a small and vulnerable subset of the population who, in addition to experiencing mental illness, have layered experiences of stigmatization and low socio-economic status. The purpose of this study was to explore the cultural context, beliefs and values underlying the CTO and perpetuated by the CTO, as it was used in community mental health care in Ontario, through an examination of its impact on identity of people living with SPMI. The study was guided by a theoretical framework that brought together the work of Michel Foucault on governmentality and Elizabeth Grosz on body image in order to critically examine the issue of identity from both the outside in (how identity is constructed) and the inside out (how that constructed identity is experienced). It used a critical ethnographic methodology. Data collection included in-depth interviews with persons with SPMI (N=7), family members (N=5) and clinicians (N=10), observations of health care practices for people with CTOs, and analysis of documents used during the CTO process. Data was analyzed using critical discourse analysis. This study revealed insights in the into social context of CTOs, that is, the complex social landscape in which CTOs operate; the social practice of CTOs, that is, the many steps and many actors involved in the CTO process; and the social impact of CTOs, that is the effect of CTO processes on both the constructed and the experienced identity of the patient, family member and clinician. The constructed identity of the patient included perceptions of the patient as risky, defective, and in need of surveillance; the experience of this identity was characterized by feelings of being criminalized, disconnected, muted, traumatized and gaslit. The constructed identity of the family members included an idealization of families as responsible and available, and instrumentalization of the family role. This identity experience was characterized as a dissonance between roles, a witnessing of the absurd, and as putting a strain on other elements of life/identity. The constructed identity of the clinician in relation to CTOs included the role of enforcer, fall-guy, paternalistic provider, and the patient’s adversary. The experience of this identity was characterized by frustration, powerlessness, distress, and an acceptance of dissonance. CTOs, while facilitating access to some treatments and services, also act to construct identities for patients that further limit their full integration into communities as valued members. An examination of the constituent parts of the CTO highlights areas in which CTO processes could be changed; research participants conveyed areas in which they thought the CTO could be improved, including changes to methods of police intervention, better collection and use of administrative data, systemic change, the use of specific approaches to care, changes to the timings of renewals, and changes to the Consent and Capacity Board hearings. The discussion highlights ways in which a re-examination of the context in which CTOs are used can lead to the consideration of political and therapeutic means to reduce both the circumstances that lead to mental and emotional distress and to improve our responses to mental and emotional distress when these are experienced by members of our communities.
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 | 0.010 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.023 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".