Should I invite them? Bystanders' inclusivity judgements towards outgroup victims and ingroup bullies in intergroup bullying
Bibliographic record
Abstract
Abstract This study examined bystanders' judgements of bullying and their inclusivity towards refugee victims and ingroup bully peers. Participants included 587 Turkish adolescents (Mage = 13.14, SD = 1.60) who were presented with two stories: intergroup (Syrian refugee victim) and intragroup (Turkish victim) bullying. They indicated acceptability of bullying, retaliation, and how likely they would be to include victims and bullies in different social contexts. Empathy, prejudice, desired social distance, and peer norms towards Syrian refugees were examined as predictors. Adolescents in schools with a higher number of Syrian peers were more likely to expect they would include the Syrian victim than adolescents in schools with a lower number of Syrian peers. Further, adolescents with higher empathy were more likely to include the Syrian victim while adolescents with higher prejudice and desired social distance were less likely to include the Syrian victim. The results highlight the importance of attending to bystanders' future interactions with victims and bullies, as bystanders have the opportunity to challenge injustice by promoting inclusive school climates in diverse societies. Please refer to the Supplementary Material section to find this article's Community and Social Impact Statement .
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".