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Record W2142989822 · doi:10.1177/0093854812439378

Assessment and Treatment of Adolescents Who Sexually Offend

2012· article· en· W2142989822 on OpenAlexaff
James R. Worling, Calvin M. Langton

Bibliographic record

VenueCriminal Justice and Behavior · 2012
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsContext (archaeology)PsychologyMotivational interviewingDistressSexual abuseAccountabilityPoison controlSex offenseSuicide preventionMedicineClinical psychologyPsychiatryMedical emergencyIntervention (counseling)

Abstract

fetched live from OpenAlex

Some adolescents who have committed a sexual crime are placed by the courts in secure residential settings. Given the heterogeneity of this client group, it is important for clinicians in these settings to complete comprehensive assessments to determine the course and content of specialized treatment, if necessary. With a focus on residential care, suggestions are provided for the assessment of strengths, risks, and needs. Particular attention is paid to issues related to informed consent, interviewing, and risk assessment. Also reviewed are various treatment issues with implications in secure settings, including the delivery of therapeutic services, use of manuals, therapeutic relationships and context, and self-care for providers. The growing evidence base for cognitive-behavioral treatment for adolescents who have sexually offended is outlined, and common treatment goals for youth who have offended sexually are critically examined. With an emphasis on treatment tailored to the unique needs of each adolescent, suggestions are offered regarding goals such as increasing accountability, recovery from posttraumatic distress, developing offense-prevention strategies, and enhancing awareness of victim impact, prosocial sexual attitudes, and healthy sexual interests. Additional issues that are considered with implications for clinicians working in secure settings include sibling sexual abuse and offenses involving child abuse imagery.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.454

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.084
GPT teacher head0.386
Teacher spread0.302 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations30
Published2012
Admission routes1
Has abstractyes

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