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Record W4412755406 · doi:10.1177/14999013251356519

University Students' Perceptions of Stalking Threat: The Role of Gender and Relationship Type

2025· article· en· W4412755406 on OpenAlexaff
Abby Vovchuk, Brianne K. Layden, Alicia Nijdam‐Jones

Bibliographic record

VenueInternational Journal of Forensic Mental Health · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicStalking, Cyberstalking, and Harassment
Canadian institutionsSimon Fraser UniversityUniversity of Manitoba
Fundersnot available
KeywordsStalkingPsychologyPerceptionSocial psychologyDevelopmental psychologyClinical psychologyCriminologyNeuroscience

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score0.200

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.372
Teacher spread0.346 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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