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Record W2981837777 · doi:10.5772/intechopen.89803

When Aggression Is Out of Control: From One-Person to Two-Person Neuropsychology

2019· book-chapter· en· W2981837777 on OpenAlexaff
Jean Gagnon, Joyce Emma Quansah, W.S. Kim

Bibliographic record

VenueIntechOpen eBooks · 2019
Typebook-chapter
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversité de MontréalCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsPsychologyAggressionNeuropsychologyExecutive functionsCognitionCognitive psychologyDevelopmental psychologySocial cognitionInhibitory controlSocial cognitive theoryPerspective (graphical)Neuroscience

Abstract

fetched live from OpenAlex

From a neuropsychological perspective, impulsive aggression and its treatment are usually conceptualized in most research as a closed executive functioning system, as though the behavior was the product of the person’s cerebral functioning only. However, recent studies in social cognitive neuroscience have emphasized the influence of social factors on cognitive processes and cerebral functioning for the development and maintenance of impulsive aggression. This chapter will review studies that highlight the relevance of initiating a shift of paradigm from a one-person-cerebral functioning model to a social interactive-cerebral functioning model of impulsive aggression. First, the influences of an aversive environment on a child’s cognitive processes and executive functioning will be discussed with the aim of explaining the development of impulsive aggressive behaviors in early childhood. Second, we will review studies that have shown how the link between social information processes and executive/inhibitory functioning serve to maintain behaviors. Finally, strengths and weaknesses of existing inhibitory control strategies will be discussed with the intention of proposing some novel ideas that incorporate a two-person neuropsychological approach.

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: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.007
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.055
GPT teacher head0.298
Teacher spread0.243 · 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 designCase report
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

Citations5
Published2019
Admission routes1
Has abstractyes

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