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Record W4389191976 · doi:10.22215/etd/2023-15667

Behind Closed Doors: Attitudes, Dark Traits, and Perceptions of Intimate Partner Sexual Violence

2023· dissertation· en· W4389191976 on OpenAlexaff
Lauren Marie Brunet

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsPsychologyPsychopathyEntitlement (fair division)BlameSexual coercionSocial psychologyNarcissismVignetteDomestic violenceDevelopmental psychologyClinical psychologyPoison controlPersonalityInjury preventionMedicine

Abstract

fetched live from OpenAlex

Intimate partner sexual violence (IPSV) is characterized by sexual violence occurring within relationships. Undergraduates (N = 680) self-reported their attitudes, behaviours, and personality and were randomly assigned to read an IPSV vignette describing a scenario of heterosexual or homosexual IPSV. Results indicated that perpetration of IPSV, non-partner coercion, rape myth acceptance, sexual entitlement, narcissism, psychopathy, sadism, and gender were significantly related to perceptions of seriousness, perpetrator, and/or victim blame; however, participants perceived the severity and blame similarly across conditions. Rape myth acceptance, sexual entitlement, and psychopathy were significant predictors of IPSV perpetration. The results demonstrate how perceived norms may influence one to blame survivors experiencing IPSV, while endorsing rape myths may lead to trivialization and perpetration. The results provide evidence for the nested ecological model framework of IPSV; additionally, practical implications include more inclusive views of sexual minority groups and raising awareness of the characteristics of IPSV perpetrators.

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)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.527
Threshold uncertainty score0.970

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 studies0.0010.000
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 head0.034
GPT teacher head0.380
Teacher spread0.345 · 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 designQualitative
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
Published2023
Admission routes1
Has abstractyes

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