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Record W7067820046

Normative influence and rational conflict decisions: Group norms and cost-benefit analyses for intergroup behavior

2005· article· en· W7067820046 on OpenAlexaboutno aff

Bibliographic record

VenueQueensland's institutional digital repository (The University of Queensland) · 2005
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsnot available
Fundersnot available
KeywordsOutgroupIngroups and outgroupsNormativeGroup conflictContext (archaeology)PerceptionExpectancy theoryValue (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

The present paper articulates a model in which ingroup and outgroup norms inform 'rational' decision-making (cost-benefit analysis) for conflict behaviors. Norms influence perceptions of the consequences of the behavior, and individuals may thus strategically conform to or violate norms in order to acquire benefits and avoid costs. Two studies demonstrate these processes in the context of conflict in Quebec. In the first study, Anglophones' perceptions of Francophone and Anglophone norms for pro-English behaviors predicted evaluations of the benefits and costs of the behaviors, and these cost-benefit evaluations in turn mediated the norm-intention links for both group norms. In the second study, a manipulated focus on supportive versus hostile ingroup and outgroup norms also predicted cost-benefit evaluations, which mediated the norm-intention relationships. The studies support a model of strategic conflict choices in which group norms inform, rather than suppress, rational expectancy value processes. Implications for theories of decision-making and normative influence are discussed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.826
Threshold uncertainty score0.687

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 studies0.0010.001
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.277
Teacher spread0.246 · 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.

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

Citations0
Published2005
Admission routes1
Has abstractyes

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