When Is It Helpful to Get Involved? Adolescents’ Perceptions of Constructive and Aggressive Bystander Support from Friends, Acquaintances, and Public Figures in Cyberbullying
Bibliographic record
Abstract
The present study examines adolescents’ perceptions of both constructive and aggressive forms of bystander support and how these perceptions differ according to whether an acquaintance of the target, a friend of the target or a public figure is providing it. Ninety-nine adolescents between 13 and 17 years old (Mage = 14.42; SD = 1.35) participated in this study. Adolescents viewed a total of nine videos, each depicting a public cyberbullying situation on Instagram and a form of constructive or aggressive bystander support from an acquaintance, a friend, or a public figure in relation to the target of cyberbullying. After each video, adolescents were asked how helpful or hurtful the bystander’s form of support was on a Likert-type scale. A significant relationship was found between the bystander’s relationship to the target, the form of support and the helpfulness of bystander support. Overall, support from friends was perceived as helpful regardless of whether it was constructive or aggressive. Moreover, it was seen as harmful for acquaintances to engage in aggressive behaviours in support of targets of cyberbullying, but generally helpful for public figures to engage in those same behaviours.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".