MétaCan
Menu
← Back to cohort
Record W2121624914 · doi:10.3138/cjccj.46.5.553

The Development of Early Delinquency: Can Classroom and School Climates Make a Difference?

2004· article· en· W2121624914 on OpenAlexaffvenueabout
Jane B. Sprott

Bibliographic record

VenueCanadian Journal of Criminology and Criminal Justice/La Revue canadienne de criminologie et de justice pénale · 2004
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsJuvenile delinquencyPsychologyDevelopmental psychologyEmotional supportPerceptionLongitudinal studySocial psychologySocial supportMedicine

Abstract

fetched live from OpenAlex

Previous research has found that school and classroom climates have important effects on children's perceptions and behaviours. More specifically, there are thought to be two types of support (emotional and instrumental) provided at the level of the classroom and the school. Emotional support within the classroom has been found to be most important for some higher-risk children. There has, however, been little research using these concepts with outcomes such as delinquency. Therefore, using two years of the Canadian National Longitudinal Survey of Children and Youth, this study investigates the role of classroom and school climates on the development of early violence and property offending. Results revealed that an emotionally supportive classroom when these children were 10 to 13 years old was related to lower levels of violence two years later, when they were 12 to 15 years old. In addition, a classroom that focused on academics (instrumental support) was predictive of lower property offending. Interpretations and policy implications are discussed.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.210
Threshold uncertainty score0.417

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.079
GPT teacher head0.305
Teacher spread0.226 · 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

Citations55
Published2004
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Criminology and Criminal Justice/La Revue canadienne de criminologie et de justice pénale→Same topicChild and Adolescent Psychosocial and Emotional Development→French-language works237,207→