Virtually Standing Up or Standing By? Correlates of Enacting Social Control Online
Bibliographic record
Abstract
Research has consistently established the robustness of the bystander effect, or the tendency of individuals to not intervene on behalf of others in emergency situations. This study examines the bystander effect in an online setting, focusing on factors that lead individuals to intervene, and therefore enact informal social control, on behalf of others who are being targeted by hate material. To address this question, we use an online survey (N=647) of youth and young adults recruited from a demographically balanced sample of Americans. Results demonstrate that the enactment of social control is positively affected by the existence of strong offline and online social bonds, collective efficacy, prior victimization, self-esteem, and an aversion for the hate material in question. Additionally, the amount of time that individuals spend online affects their likelihood of intervention. These findings provide important insights into the processes that underlie informal social control and begin to bridge the gap in knowledge between social control in the physical and virtual realms.
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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 | 0.001 | 0.012 |
| 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 | 0.002 | 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".