Are we all in this together? Co‐victimization, inclusive social identity and collective action in solidarity with the disadvantaged
Bibliographic record
Abstract
Common experience of injustice can be a potent motivator of collective action and efforts to achieve social change - and of such efforts becoming more widespread. In this research, we propose that the effects of co-victimization on collective action are a function of inclusive social identity. Experiment 1 (N= 61) demonstrated that while presence (compared to absence) of co-victimization positively predicted consumer (i.e., participants) willingness to act collectively in solidarity with sweatshop workers, this effect was mediated by inclusive social identity. In Experiment 2 (N= 120), the salience of inclusive social identity was experimentally manipulated and interacted with co-victimization to predict collective action. When inclusive social identity was salient, co-victimization enhanced collective action, including willingness to pay extra for products made ethically and in support of fair wages for workers. In contrast, collective action was attenuated when co-victimization took place in the absence of inclusive social identity. Implications for understanding when co-victimization is transformed into common fate and political solidarity with the disadvantaged 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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".