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Record W2934167774 · doi:10.1080/01639625.2019.1596534

Childhood Trauma, Criminogenic Social Schemas, and Violent Crime

2019· article· en· W2934167774 on OpenAlexaff
Stephen W. Baron, David R. Forde

Bibliographic record

VenueDeviant Behavior · 2019
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsQueen's University
Fundersnot available
KeywordsNeglectPsychologyChildhood abuseSexual abuseChild abuseViolent crimeDevelopmental psychologyPhysical abusePoison controlInjury preventionCriminologyPsychiatryMedical emergencyMedicine

Abstract

fetched live from OpenAlex

Utilizing a sample of 400 homeless street youth, the study draws on the social schematic theory of crime to examine if childhood trauma (physical abuse, physical neglect, emotional neglect, and sexual abuse) is linked to the development of a criminogenic knowledge structure (CKS) that mediates its relationship with violence. Results indicate childhood trauma is directly associated with the CKS. They also show that it is indirectly related through violent peers. The CKS in turn is directly linked to violence as are childhood trauma and violent peers. The CKS also mediates the relationship childhood trauma and violent peers have with violence. Violent peers likewise mediate the association between childhood trauma and violence. The link between childhood trauma and violence is also serially mediated through violent peers and the CKS. Findings suggest the social schematic theory offers a valuable explanation for the link between childhood trauma and violence.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.301
Teacher spread0.271 · 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

Citations23
Published2019
Admission routes1
Has abstractyes

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