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Record W2154467372 · doi:10.1177/1541204012457960

Institutional Offense Patterns in Adolescent Offenders

2012· article· en· W2154467372 on OpenAlexaff
Ainslie McDougall, Mary Ann Campbell, Darcy A. Santor

Bibliographic record

VenueYouth Violence and Juvenile Justice · 2012
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of OttawaUniversity of New Brunswick
Fundersnot available
KeywordsMisconductPsychologyJuvenile delinquencyMental healthPsychiatryPsychological interventionClinical psychologySuicide preventionAnxietyPoison controlOccupational safety and healthInjury preventionHuman factors and ergonomicsMedicineMedical emergencyPolitical science

Abstract

fetched live from OpenAlex

The current study compared the antisocial and mental health functioning of incarcerated adolescents with histories of serious and persistent institutional misconduct to those with histories of minor forms of institutional misconduct. Institutional offense histories of 192 incarcerated adolescent offenders (84.5% male) were reviewed and their mental health was assessed using the Youth Self-Report (YSR) to determine whether mental health factors were more prevalent in serious/persistent institutional offenders. Youths with a history of serious/prolific institutional offending were younger at first arrest, had more convictions, spent more time incarcerated, and scored higher on YSR aggression and delinquency subscales than those with low/moderate institutional offending. Although antisociality is likely a major contributor to serious and persistent forms of institutional misconduct, these youths, especially the females, had significantly higher YSR anxiety/depression symptoms than the low/moderate institutional offending group. Although traditional criminogenic factors may be more salient to the risk of institutional misconduct, mental health should remain an important area of case management given its comorbidity with higher levels of misconduct and its potential impact on youths' responsivity to interventions focusing on criminogenic needs.

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 score0.099
Threshold uncertainty score0.587

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 head0.048
GPT teacher head0.293
Teacher spread0.245 · 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

Citations3
Published2012
Admission routes1
Has abstractyes

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