Grumbling, voting, demonstrating, and rioting : a model of social identity and decision-making in intergroup contexts
Bibliographic record
Abstract
An individual faced with intergroup conflict must choose from a vast array of possible actions, ranging from grumbling among ingroup friends to voting and demonstrating to rioting and revolution. The present thesis proposes a model of decision-making in intergroup contexts oriented towards understanding how group members choose among these behavioural alternatives. Intergroup decisions are conceptualized as rationally shaped by perceptions of the benefits and costs associated with the action (expectancy-value processes). In intergroup contexts, group-level costs and benefits may play a critical role in individuals' decision-making. Perception of the dynamic between ingroup and outgroup norms is thought to be a key determinant of the group-level benefits and costs associated with individualistic or collective actions. Four studies explore the predictive value of this model for understanding decision-making in the context of English-French conflict in Quebec. Studies 1 and 2 provide evidence that group-level costs and benefits influence individuals' decision-making, in intergroup contexts. Contrary to the predictions of individualistic models of decision-making such as the theory of planned behaviour (Ajzen, 1985), the individual level of analysis was not observed to mediate the group level of analysis. Moreover, contrary to recent social identity theorizing (Kelly, 1993; Simon et al., 1998), perceived group-level costs and benefits were implicated in the relationship between social identity and intentions to engage in collective action. Studies 3 and 4 provide evidence that outgroup and ingroup norms may interact to influence decision-making. Thus, contrary to the referent informational influence model (Terry & Hogg, 1996; Turner, 1991), ingroup norms alone did not determine group members' actions. Moreover, Study 4 provides evidence that the dynamic between ingroup and outgroup norms influences evaluations of the costs and benefits of intergroup behaviours, both
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".