University Students' Perceptions of Stalking Threat: The Role of Gender and Relationship Type
Bibliographic record
Abstract
Perceived threat regarding stalking behaviours stems from stalking stereotypes involving gendered dyads, often with men as the perpetrators and women as victims. As limited research has examined threat perceptions that deviate from this dyad, the present study investigated whether same-gender and non-binary stalking dyads are perceived as less threatening than man-to-woman dyads. University students ( N = 243) completed a vignette survey manipulating perpetrator gender, victim gender and relationship type. Quantitative analyses revealed that perpetrator gender and relationship type affected perceived threat, with victim gender only being significant when interacting with the perpetrator's gender. Men perpetrators categorized as strangers were rated with the highest perceived threat compared to all other dyads. The study's findings suggest that gender identification and relationship type impact perceptions of stalking threat. As our understanding of gender diversity expands, the legal system must evolve by investigating a variety of perpetrators and relationships to better support responses to stalking to avoid further harm to victims outside of man-to-woman stalking dyads.
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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 | 0.007 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".