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Record W2165765985 · doi:10.1111/1467-8624.00508

Group Size Regulates Self–Assertive versus Self–Deprecating Responses to Interpersonal Competition

2002· article· en· W2165765985 on OpenAlexafffund
Joyce F. Benenson, Rebecca Maiese, Eva Dolenszky, Nicole Dolensky, Nancy Sinclair, Anna Simpson

Bibliographic record

VenueChild Development · 2002
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsMcGill University
FundersMcGill University
KeywordsPsychologyAssertivenessInterpersonal communicationContext (archaeology)Developmental psychologyCompetition (biology)Social psychologyInterpersonal relationshipEcology

Abstract

fetched live from OpenAlex

The current study examined the hypothesis that group size can influence whether children display self-assertive versus self-deprecating responses to interpersonal competition, especially under stress. Twenty same-sex play-groups (N = 120) of 9- to 10-year-old children played a competitive game in groups and in dyads. Stress was induced by causing some of the children to lose the game and watch as their opponents received psychological and material rewards. Results demonstrated that both the dynamics of the game and individual reactions to stress varied consistently as a function of the social context. Individuals displayed more assertive behaviors in groups than in dyads. In contrast, individuals exhibited more self-deprecating behaviors in dyads than in groups. Given that under naturalistic conditions males are more likely than are females to interact in groups and females are more likely than are males to interact in dyads, group size provides one possible mechanism for the development of sex differences in self-assertive versus self-deprecating behaviors.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.751
Threshold uncertainty score0.998

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)0.0030.001

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 head0.020
GPT teacher head0.271
Teacher spread0.250 · 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

Citations31
Published2002
Admission routes2
Has abstractyes

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