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Developmental Origins of Chronic Physical Aggression: A Bio-Psycho-Social Model for the Next Generation of Preventive Interventions

2017· review· en· W2613741790 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

VenueAnnual Review of Psychology · 2017
Typereview
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsAggressionPsychologyDevelopmental psychologyInheritance (genetic algorithm)Psychological interventionPsychiatryGenetics

Abstract

fetched live from OpenAlex

This review describes a bio-psycho-social approach to understanding and preventing the development of chronic physical aggression. The debate on the developmental origins of aggression has historically opposed genetic and environmental mechanisms. Recent studies have shown that the frequency of physical aggression peaks in early childhood and then decreases until old age. Molecular genetic studies and twin studies have confirmed important genetic influences. However, recent epigenetic studies have highlighted the important role of environments in gene expression and brain development. These studies suggest that interrelated bio-psycho-social channels involved in the development of chronic physical aggression are generally the product of an intergenerational transmission process occurring through assortative mating, genetic inheritance, and the inheritance of physical and social environmental conditions that handicap brain functioning and support the use of physical aggression to solve problems. Given these intergenerational mechanisms and physical aggression onset in infancy, it appears clear that preventive interventions should start early in pregnancy, at the latest.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.893
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.314
GPT teacher head0.506
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