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Record W1977528823 · doi:10.1037/a0033617

Reciprocating risks of peer problems and aggression for children’s internalizing problems.

2013· article· en· W1977528823 on OpenAlexafffund
Wendy L. G. Hoglund, Courtney A. Chisholm

Bibliographic record

VenueDevelopmental Psychology · 2013
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyAggressionPeer victimizationAnxietyDevelopmental psychologyPeer groupEthnically diversePoison controlInjury preventionClinical psychologyPsychiatryDemographyPopulation

Abstract

fetched live from OpenAlex

Three complementary models of how peer relationship problems (exclusion and victimization) and aggressive behaviors relate to prospective levels of internalizing problems are examined. The additive risks model proposes that peer problems and aggression cumulatively increase risks for internalizing problems. The reciprocal risks model hypothesizes that peer problems and aggression transact over time and mediate the effects of each other on prospective internalizing problems. Last, the internalizing risks model proposes that, in addition to aggressive behaviors, prior internalizing problems also provoke peer problems that, in turn, further elevate risks for prospective internalizing problems. Data came from a sample of 453 low-income, ethnically diverse children in kindergarten to Grade 3 who were assessed 3 times over 1 school term (in January, March and June). Findings supported the internalizing risks model. Four key pathways were found to increase risks for internalizing problems by the end of the school year; 2 of these routes were rooted in aggressive behaviors, and 3 paths operated indirectly via levels of peer problems in the spring. Children who were initially aggressive became excluded by peers by the spring, whereas children who initially showed more symptoms of depression and anxiety became victimized by peers by the spring. In turn, both peer exclusion and victimization increased prospective levels of internalizing problems by the end of the school year.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.282
Threshold uncertainty score1.000

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)0.0010.000

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 head0.073
GPT teacher head0.361
Teacher spread0.288 · 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 teacher head, not a consensus.

Study designObservational
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

Citations45
Published2013
Admission routes2
Has abstractyes

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