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Record W4243152558 · doi:10.3886/icpsr30143

Criminal Justice Drug Abuse Treatment Studies (CJ-DATS): A Comparison of Two Reentry Strategies for Drug Abusing Juvenile Offenders, 2003-2009 [United States]

2014· dataset· en· W4243152558 on OpenAlexaff
Nancy Jainchill

Bibliographic record

VenueICPSR Data Holdings · 2014
Typedataset
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsChild, Adolescent and Family Mental Health
Fundersnot available
KeywordsJuvenileReentryCriminal justiceCriminologyDrugSubstance abuseEconomic JusticePsychologyPsychiatryMedicinePolitical scienceLawInternal medicineBiology

Abstract

fetched live from OpenAlex

Despite progress in reducing crime, crime rates among juveniles, particularly non-white juveniles, remain high. A number of programs have been developed to address the process of reintegration into the community, known as aftercare, through resource efficiency, recidivism reduction, and public safety. This study attempts to evaluate the relative effectiveness of two strategies, extant aftercare services (AS) and Cognitive Restructuring (CR), in order to determine the differential effects on juveniles with varying problem profiles. 236 baseline interviews took place, after which 118 individuals were assigned to CR and 118 to AS. They were then interviewed at three months, two weeks prior to completion of the treatment, and nine months after the completion of the treatment. The two treatments were then compared for relative effectiveness and for relative quality of integration into the juvenile justice system. This data is public use. There are 62 variables and 65 cases in Recruitment(DS1). Intake (DS2) has 444 variables and 187 respondents. The Three Month Follow-Up (DS3) has 319 variables and 159 respondents. Finally, there are 319 variables and 137 respondents in the Nine Month Follow-Up (DS4).

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.088
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.000
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 head0.141
GPT teacher head0.420
Teacher spread0.279 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2014
Admission routes1
Has abstractyes

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