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Record W2116380220 · doi:10.1017/s0954579414001394

The effects of violence exposure on the development of impulse control and future orientation across adolescence and early adulthood: Time-specific and generalized effects in a sample of juvenile offenders

2015· article· en· W2116380220 on OpenAlexaff
Kathryn C. Monahan, Kevin M. King, Elizabeth P. Shulman, Elizabeth Cauffman, Laurie Chassin

Bibliographic record

VenueDevelopment and Psychopathology · 2015
Typearticle
Languageen
FieldPsychology
TopicPsychological and Temporal Perspectives Research
Canadian institutionsBrock University
FundersNational Institute on Drug Abuse
KeywordsImpulse controlPsychologyFuture orientationImpulse (physics)JuvenileDevelopmental psychologyOperationalizationOrientation (vector space)Early adulthoodInjury preventionPoison controlYoung adultSocial psychologyPsychiatryMedical emergencyMedicine

Abstract

fetched live from OpenAlex

Impulse control and future orientation increase across adolescence, but little is known about how contextual factors shape the development of these capacities. The present study investigates how stress exposure, operationalized as exposure to violence, alters the developmental pattern of impulse control and future orientation across adolescence and early adulthood. In a sample of 1,354 serious juvenile offenders, higher exposure to violence was associated with lower levels of future orientation at age 15 and suppressed development of future orientation from ages 15 to 25. Increases in witnessing violence or victimization were linked to declines in impulse control 1 year later, but only during adolescence. Thus, beyond previous experiences of exposure to violence, witnessing violence and victimization during adolescence conveys unique risk for suppressed development of self-regulation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.308
Teacher spread0.285 · 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 source (direct Gemma or distilled Codex), 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

Citations81
Published2015
Admission routes1
Has abstractyes

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