Normative influence and rational conflict decisions: Group norms and cost-benefit analyses for intergroup behaviour
Bibliographic record
Abstract
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 Québec. 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".