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Aggressive and Violent Behavior

2015· other· en· W1944881347 on OpenAlexaff
Manuel Eisner, Tina Malti

Bibliographic record

Venuenot available
Typeother
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAggressionPsychologyNormativeDevelopmental psychologySocializationEmpirical researchPolitical science

Abstract

fetched live from OpenAlex

Abstract This chapter reviews research and theory on the development of aggressive behavior and violence from childhood to adolescence. We also summarize and discuss research on correlates, risk factors, markers, causal mechanisms, and consequences of aggressive behavior and violence. Due to space constraints, our review focuses on more recent developmental research and theoretical advancements in the past decade. In the introductory section, we present definitions and dimensions of aggression across development. Then we discuss current theories on adaptive and maladaptive functions of human aggression, and we identify cross‐cutting theoretical issues. Next, we describe subtypes of aggression, clinical classification, and measurement issues. Then the empirical literature related to the epidemiology of aggression from infancy to adolescence is reviewed, with a focus on normative developmental change and stability. The subsequent sections review the biological, individual, and socialization processes that are related to the development of aggressive behavior and violence. Lastly, we review macro‐level comparative research on aggression and violence. Finally, we discuss challenges in current research and identify areas for future research.

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)0.000
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: Other · Consensus signal: Other
Teacher disagreement score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.023
GPT teacher head0.318
Teacher spread0.295 · 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
GenreOther

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

Citations121
Published2015
Admission routes1
Has abstractyes

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