The impact of onlooking and including bystander behaviour on judgments and emotions regarding peer exclusion
Bibliographic record
Abstract
We investigated judgments and emotions in contexts of social exclusion that varied as a function of bystander behaviour (N = 173, 12- and 16-year-olds). Adolescents responded to film vignettes depicting a target excluded by a group with no bystanders, onlooking bystanders, or bystanders who included the target. Adolescents were asked to judge the behaviour and attribute emotions to the excluding group, the excluded target, and the bystanders. Younger adolescents judged the behaviour of the excluding group as more wrong than older adolescents when there were no bystanders present, indicating that the presence of bystanders was viewed as lessening the negative outcome of exclusion by the younger group. Yet, bystanders play a positive role only when they are includers, not when they are silent observers. This distinction was revealed by the findings that adolescents rated the behaviour of onlooking bystanders as more wrong compared with the behaviour of including bystanders. Moreover, all adolescents justified the inclusive behaviour more frequently with empathy than the onlooking behaviour. Adolescents also anticipated more empathy to including bystanders than to onlooking bystanders, as well as anticipated more guilt to onlooking bystanders than including bystanders. The findings are discussed in light of the role of group norms and group processes regarding bystanders' roles in social exclusion peer encounters.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".