Risks of Recidivism in Criminally Involved Persons With Addiction at Risk of Deportation: A Case Commentary and Review
Bibliographic record
Abstract
ABSTRACT A clinical case is presented for a patient in sustained remission from opioid use disorder following 12 months of evidence-based treatment who faces deportation due to criminal behavior conducted whilst in active and untreated addiction. A review of the criminal justice and addiction literature suggests that the chance of relapse and recidivism to criminal behavior is low when engaged in evidence-based addiction treatment for over 12 months. Deportation has been shown to disrupt recovery activity and increase recidivism and relapse risk. As addiction is widely now understood to be a disease based in neurobiology, and treatable, we believe that the evidence supports our assertion of deportation as a cruel and unjust treatment of a chronic disease. La présentation du cas clinique d’un patient en rémission prolongée causé par un trouble lié à l’usage d’opioïdes. Après 12 mois de traitement fondé sur des données probantes, le patient risque l’expulsion en raison d’un comportement criminel mené alors qu’il était dans une dépendance active et non traitée. Une revue de la justice pénale et de la littérature sur l’addiction suggère que le risque de rechute et de récidive au comportement criminel est faible lorsque le patient est engagé dans un traitement de l’addiction fondé sur des données probantes pendant plus de 12 mois. Il a été démontré que l’expulsion perturbe les activités de rétablissement et augmente les risques de récidive et de rechute. Comme l’addiction est désormais largement comprise comme une maladie basée sur la neurobiologie et traitable, nous pensons que la preuve étaye notre affirmation selon laquelle l’expulsion est un traitement cruel et injuste d’une maladie chronique.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".