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Record W2151444674 · doi:10.1002/bsl.835

Synthesis of studies of co‐occurring disorder(s) in criminal justice and a research agenda

2008· review· en· W2151444674 on OpenAlexaff
Stanley Sacks, Gerald Melnick, Christine E. Grella

Bibliographic record

VenueBehavioral Sciences & the Law · 2008
Typereview
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsContext (archaeology)Criminal justiceCriminologyEconomic JusticeSpecial sectionPsychiatrySubstance abusePopulationPolitical scienceMedicinePsychologyEngineeringLawEnvironmental health

Abstract

fetched live from OpenAlex

The studies reported in this special issue were designed to take advantage of the unique opportunity that the Criminal Justice Drug Abuse Treatment Studies (CJDATS) cooperative provides to the systematic study of several key issues in programming for co-occurring disorder(s) (COD) in the criminal justice system. These papers present findings from CJDATS studies pertaining to co-occurring disorder(s), identify clinical initiatives to strengthen efforts to treat the population with co-occurring disorder(s), and point to a direction for the elaboration of a future research agenda. Four key areas of investigation are presented: Screening and Diagnosis; the Relationship of Co-Occurring Disorder(s) to Violence; Gender Differences; and the Delivery of Services for Co-Occurring Disorder(s). The first section of this article summarizes the studies included in this special issue within the context of the research literature already available. The second section suggests a future research agenda for the study of offender populations with co-occurring disorder(s), and concludes with a broad statement of clinical advancements to date.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.936
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.002
Science and technology studies0.0000.006
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.506
GPT teacher head0.567
Teacher spread0.061 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations4
Published2008
Admission routes1
Has abstractyes

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