Cyber-Bystander Behavior Among Canadian and Iranian Youth: The Influence of Bystander Type and Relationship to the Perpetrator on Moral Responsibility
Why this work is in the frame
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Bibliographic record
Abstract
The current study examines how social determinants influence the way youth from Canadian and Iranian contexts evaluate and morally disengage as bystanders of cyberbullying. While Iranian culture differs from other individualistic and collectivist cultures, Iranian youth have become just as technologically acculturated as their global peers. Despite this, less is understood about how Iranian youth respond to cyberbullying in comparison to youth from individualistic societies. Participants from Canada ( N = 60) and Iran ( N = 59) who were between the ages of 8-to-15 years old ( N = 119, M = 11.33 years, SD = 1.63 years) read 6 cyberbullying scenarios that varied according to Bystander Relationship to Perpetrator (Acquaintance or Friend) and Bystander Response (Assists Cyberbully, Does Nothing, Defends Victim). After reading each scenario, participants were asked to evaluate the bystander's behavior. They were also asked how they would feel if they were the bystander. Similar to past research, these responses were coded on a continuous scale ranging from morally disengaged to morally responsible. Overall, Canadians were more critical of passive bystander behaviors and more supportive toward defending behaviors compared to Iranians. Iranians were more supportive of the behaviors of bystanders who were friends of perpetrators than Canadians were, and Iranians were more critical toward acquaintances of perpetrators. Significant interactions were also found between participants' country of origin, the bystander's relationship with the perpetrator and the bystander's behavior. Taken together, these findings highlight the importance of differentiating between negative judgments and moral attributions of bystander responses.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it