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Record W2964533734 · doi:10.1093/bjc/azz053

Prevention of Criminal Offending: The Intervening and Protective Effects of Education for Aggressive Youth

2019· article· en· W2964533734 on OpenAlexafffund
Kathleen Kennedy-Turner, Lisa A. Serbin, Dale M. Stack, Daniel J. Dickson, Jane E. Ledingham, Alex E. Schwartzman

Bibliographic record

VenueThe British Journal of Criminology · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsUniversity of OttawaConcordia University
FundersCanadian Institutes of Health Research
KeywordsModerationPsychologyAggressionOddsDisadvantageNeighbourhood (mathematics)Developmental psychologyInjury preventionParental supervisionPoison controlMedicineSocial psychologyLogistic regressionMedical emergencyPolitical science

Abstract

fetched live from OpenAlex

Abstract Children from poor neighbourhoods showing early aggressive behaviour are at risk for criminal offending. The role of education as a mediator, neighbourhood disadvantage and aggression as moderators for criminal offending were examined in a lower-income, community sample (n = 3,521; 48% males), across a 40-year period from childhood to mid-adulthood. Educational attainment accounted for 15–59% of the effect from childhood risk factors. Aggression was found to be a moderator such that aggressive children with low education had the highest odds of criminal offending. A protective effect was found where aggressive children who managed to obtain more education had reduced odds of offending. Research conceptualizing education as a ‘control’ variable does not address its role in the processes leading to criminal offending.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.851
Threshold uncertainty score0.222

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.071
GPT teacher head0.365
Teacher spread0.294 · 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 designOther design
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

Citations17
Published2019
Admission routes2
Has abstractyes

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