What's Love Got To Do With It? An Examination of Perceived Prosocial Motivations for the Perpetration of Intimate Partner Cyber Aggression
Bibliographic record
Abstract
Recent technological advancements have facilitated cyber relationships and in turn, cyber dating abuse has become more prevalent than ever. The present study examined cyber aggression perpetration in the form of excessive monitoring as a function of perceived prosocial motives. It was hypothesized that perpetrators reporting prosocial motivations would be significantly related to high levels of perpetration. Additionally, relationship investment was predicted to be a moderator of the relationship between perceived prosocial motives and perpetration. The third hypothesis was that gender would moderate the relationship, such that females would exhibit a stronger relationship than males. To examine these hypotheses, undergraduate university students (N = 513) completed questionnaires reporting the frequency and type of cyber dating abuse they perpetrated, the underlying motivations perpetrators reported lead to perpetration, and relationship investment. This research has relevant implications for the development of intervention and prevention programs aimed at reducing the occurrence of online dating violence.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".