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Record W2030638117 · doi:10.1108/09578230310504652

Students’ antisocial and aggressive behavior: development and prediction

2003· article· en· W2030638117 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Educational Administration · 2003
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPsychologyDevelopmental psychologyAntisocial personality disorderJuvenile delinquencyAggressionConduct disorderPoison controlInjury preventionMedicine

Abstract

fetched live from OpenAlex

Students’ antisocial behavior can often lead to violence in school. Longitudinal studies pertaining to antisocial behavior have contributed considerably to the development of knowledge in this field of research. This knowledge now enables us to identify the different developmental stages of aggressive and antisocial behavior during childhood and adolescence. Consequently, we are better able to identify antisocial behavior in the classroom, to describe the developmental pathways leading to antisocial behavior, to identify the risk factors relating to this issue and finally, to predict who might be at‐risk of developing antisocial behavior. In the past, antisocial behavior was conceived as following a single developmental pathway encompassing several categories of behavioral problems. Now, on the other hand, many studies demonstrate how the development of these behaviors can be explained through different pathways.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.018
Threshold uncertainty score0.478

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.023
GPT teacher head0.351
Teacher spread0.328 · 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