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Record W7045754192

Cognitive-behavioral program for young offenders : by focusing on the peer helping approach

2017· dissertation· en· W7045754192 on OpenAlexaboutno aff

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2017
Typedissertation
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsnot available
Fundersnot available
KeywordsThunderPeer groupCognitionAngerCognitive restructuringPositive Youth DevelopmentSocial skillsControl (management)Social cognitive theoryJuvenile delinquency
DOInot available

Abstract

fetched live from OpenAlex

The present study evaluated a newly developed cognitive behavioral program, the Equip
\nprogram (Gibbs, Potter & Goldstein, 1995), that focuses on teaching youth to think and act
\nresponsibly through a peer helping approach. The 10-week program, which includes
\ncomponents of anger management, social skills training and moral development was
\nimplemented with a group of moderate to high risk young offenders in a secure custody facility
\nin Thunder Bay, Ontario. The Equip program was compared to an alternative cognitive
\nbehavioral program currently implemented with young offenders in the Thunder Bay area and a
\ncontrol group consisting of youth serving probation sentences in the community and receiving
\nminimal intervention. Pre and post measures o f social skills, cognitive distortions and behavioral
\noutcomes indicated that relative to the control group. Equip members evidenced significant gains
\nin overall levels of social skills and skills involved in dealing with peer pressure. Although no
\nbehavioral gains were found, results also revealed clinically significant improvements in
\ncognitive distortions for the alternative treatment group, providing support for the use of
\ncognitively based programs with young offenders.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.627
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.001
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 head0.103
GPT teacher head0.366
Teacher spread0.262 · 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
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

Citations0
Published2017
Admission routes1
Has abstractyes

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