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The Role of Anxiety in Coercive Family Processes with Aggressive Children

2015· book· en· W2178439525 on OpenAlexaff
Isabela Granic, Jessica P. Lougheed

Bibliographic record

VenueOxford University Press eBooks · 2015
Typebook
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsQueen's University
Fundersnot available
KeywordsAggressionAnxietyPsychologyExtant taxonDevelopmental psychologyPermissiveCoercion (linguistics)Childhood developmentClinical psychologySocial psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

The majority of aggressive children exhibit symptoms of anxiety. This chapter outlines a novel theoretical model that builds explicitly on coercion theory, linking aggression with the regulation of anxiety in both caregivers and children. Three hypotheses are suggested and data are applied to support this model: (1) unpredictable oscillations between permissive and hostile parenting (two distinct aspects of the coercive cycle) induces anxiety in children, which in turn triggers aggressive behavior; (2) peer relations and difficult school contexts exacerbate anxiety, which in turn may trigger bouts of aggression that function as regulation for distressing emotions; and (3) to improve the efficacy of treatments for childhood aggression, anxiety needs to be one of the primary targets of treatment. Almost no research has directly tested these hypotheses, but the chapter reviews extant research and theory consistent with these claims and suggests future research designs that can test them specifically.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.212
Teacher spread0.200 · 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 designQualitative
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

Citations9
Published2015
Admission routes1
Has abstractyes

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