MétaCan
Menu
Back to cohort
Record W2290443260 · doi:10.14288/1.0106890

Pre-delinquency: its recognition in school

2012· article· en· W2290443260 on OpenAlexaboutno aff
Gerard George Myers

Bibliographic record

VenuecIRcle (University of British Columbia) · 2012
Typearticle
Languageen
FieldComputer Science
TopicEducational Challenges and Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsJuvenile delinquencyCriminologyPsychologyComputer scienceComputer security

Abstract

fetched live from OpenAlex

This study is primarily concerned with the early recognition of symptomatic behaviour in school, and subsequent treatment of the child who may become delinquent. It is based upon the premise that the only effective method of control of juvenile delinquency lies in prevention. The findings are based upon investigation of a sample group of delinquents from the Vancouver Juvenile Court, and a smaller group of delinquents from the same sample, studied in the city schools. The progressive development of delinquency is traced, from its origin in emotional factors, through the school years, to the ultimate conflict with the law. The study indicates the behaviour characteristics of many pre-delinquent children in school, and the extent to which these attributes are recognizable as symptomatic patterns. The attitudes of teachers toward troublesome behaviour in school are discussed with reference to the feasibility of a collaborative approach, between the social worker and the teacher, to the problem of prevention. In its theoretical aspects, the study draws from reports of current programs in delinquency control, with emphasis upon their preventive content. The analysis of the various control measures shows their limited recognition of the deeper-lying emotional basis of delinquent behaviour. An outline for a preventive program is presented. It is based upon the conditions indicated by the study, and the resources available to such a program in the city of Vancouver. The outline suggests how a preventive program may be launched on an experimental basis, through a reorganization of existing agencies and services.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.251
Threshold uncertainty score0.498

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.222
Teacher spread0.192 · 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 designNot applicable
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

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same venuecIRcle (University of British Columbia)Same topicEducational Challenges and InnovationsFrench-language works237,207