"EU NÃO SOU UMA DROGA": um diálogo hermenêutico sobre o GAM no CAPS AD
Bibliographic record
Abstract
Autonomous Medication Management (GAM) is an emancipatory care strategy in mental health, developed in Canada and adapted to the Brazilian context, aimed at producing user au- tonomy in the context of their care. Based on the challenges of care in freedom arising from the process of the Brazilian Psychiatric Reform, there has been a growing concern about the non- critical use of psychiatric drugs in mental health services. On the other hand, the issue of con- sumption of other drugs, especially illicit drugs, has taken center stage in counter-reform move- ments, advancing the discussion on human rights in a context of greater vulnerability. In this study, we start from a little depth questioning in the literature that proposes an approximation between these issues based on the identification of the contributions of the implementation of the GAM strategy, in the organization of a reference Psychosocial Care Center for the care of people with related problems to the use of drugs (CAPS AD), paying attention to possible pe- culiarities of the field of alcohol and other drugs. This is a qualitative study, based on critical and narrative hermeneutics, in the light of contemporary philosophers Hanz George Gadamer and Paul Ricoeur. The procedures used to produce the data were the realization of a focus group with the workers and the recording in the field diary of the experience of conducting a GAM group at CAPS AD in the city of Santos / SP. The interpretative hermeneutic exercise involved the organization of the main argument centers, followed by narrative constructions elaborated by the researcher. From this material produced, we sought to produce a dialogue between users and workers, highlighting the main approaches and distances between these productions and relating them to authors who dialogue with the theme of alcohol and other drugs. The research results point to the experience of high vulnerability and criminalization of drug users and the recurrent hospitalizations in Therapeutic Communities, in response to poverty, denounce the precariousness of health services and the absence of other public policies, in addition to their repercussion on discontinuity. care. They also show a devaluation of the user's biography in the medical posture, as well as the predominance / prioritization of drug treatment in the CAPS AD and indicate the need to radicalize the discussion of these prescriptions and reorganize the care offers, allowing the exercise of co-management in the service.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".