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Record W2760288026

The Integrated Risk Assessment and Treatment System (IRATS) Model of Sexual Offending: A Case Study

2017· article· en· W2760288026 on OpenAlex
Jeff Abracen, Jan Looman, Allessandra Gallo

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMedical Research Archives · 2017
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsProvidence Health Care
Fundersnot available
KeywordsOutcome (game theory)PsychologyRisk assessmentSex offenderRisk modelClinical psychologyMedicineComputer scienceRisk analysis (engineering)Computer security
DOInot available

Abstract

fetched live from OpenAlex

The present article describes the Integrated Risk Assessment and Treatment System (IRATS) Model of offender therapy. The model was developed for use with sexual offenders though we have argued elsewhere (e.g., Abracen and Looman, 2016) that the model may be easily adapted for use with violent non-sexual offenders. Although this model has been described in detail elsewhere, the present manuscript presents an illustration of the clinical uses of the model as applied to a particular client. This client has been included in the various outcome studies that the authors have completed on high-risk high-need sexual offenders seen in both institutional and community settings. Following a discussion of the case of GW we review some of the outcome research which we have completed in support of the model.

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.

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)0.005
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.798
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.180
GPT teacher head0.491
Teacher spread0.311 · 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