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Record W2894685103

Children’s Social Cognitions:Physically and Relationally Aggressive Strategiesand Children’s Goals in Peer Conflict Situations

2000· article· W2894685103 on OpenAlexaff
Kendra D. Delveaux, Tina Daniels

Bibliographic record

VenueDigitalCommons - WayneState (Wayne State University) · 2000
Typearticle
Language
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsCarleton University
Fundersnot available
KeywordsPsychologyProsocial behaviorCognitionDevelopmental psychologyConflict resolutionAggressionSocial psychologyPeer victimizationSocial cognitionHuman factors and ergonomicsPoison control
DOInot available

Abstract

fetched live from OpenAlex

The relation between goals and strategies for conflict resolution of children in the 4th through 6th grades were assessed using self-report questionnaires (N 273). Prosocial strategies were positively correlated with relationship and equality goals, whereas aggressive strategies (physical and relational) were related to self-interest, control, and revenge goals. Relationally aggressive strategies were more strongly associated with the goals of avoiding trouble and maintaining relationships among the peer group than were physically aggressive strategies. Also, boys were more likely to endorse physically aggressive strategies, whereas girls reported greater endorsement of prosocial strategies, but no gender differences were discovered in children’s ratings of relationally aggressive strategies. Results are discussed in terms of the relevance of children’s social cognitions to the study of physically and relationally aggressive behavior.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.016
GPT teacher head0.249
Teacher spread0.233 · 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 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

Citations80
Published2000
Admission routes1
Has abstractyes

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