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Record W1983138849 · doi:10.1177/0093854809333958

Psychopathic Traits and Perceptions of Victim Vulnerability

2009· article· en· W1983138849 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCriminal Justice and Behavior · 2009
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsBrock University
Fundersnot available
KeywordsPsychopathyVulnerability (computing)PsychologyPoison controlHuman factors and ergonomicsPerceptionInjury preventionClinical psychologyDevelopmental psychologySocial psychologyComputer securityPersonalityMedicineComputer scienceMedical emergency

Abstract

fetched live from OpenAlex

This study examines whether psychopathic traits in a nonreferred (and presumably nonpsychopathic) sample could enhance the accuracy of perceptions of victim vulnerability. In a previous study, the interpersonal and affective component of psychopathy was associated with increased accuracy in assessing vulnerability in dyadic conversations, and Grayson and Stein (1981) established that vulnerability could be assessed by observing targets walking. The purpose of this study was to determine whether individuals scoring higher on psychopathic traits would be better able to judge vulnerability to victimization after viewing short clips of targets walking. Participants provided a vulnerability estimate for each target and completed the Self-Report Psychopathy Scale: Version III (SRP-III). Higher SRP-III scores were associated with greater accuracy in assessing targets' vulnerability to victimization. Implications for the prevention of victimization are discussed.

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.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.941
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.042
GPT teacher head0.366
Teacher spread0.324 · 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