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Record W4221117774 · doi:10.1017/epi.2022.5

Rape Myths, Catastrophe, and Credibility

2022· article· en· W4221117774 on OpenAlex
Emily C. R. Tilton

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

VenueEpisteme · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicFeminist Epistemology and Gender Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMythologyInjusticeSeriousnessCredibilityCriminologyPsychologyPrejudice (legal term)Social psychologySociologyLawPolitical scienceHistory

Abstract

fetched live from OpenAlex

Abstract There is an undeniable tendency to dismiss women's sexual assault allegations out of hand. However, this tendency is not monolithic – allegations that black men have raped white women are often met with deadly seriousness. I argue that contemporary rape culture is characterized by the interplay between rape myths that minimize rape, and myths that catastrophize rape. Together, these two sets of rape myths distort the epistemic resources that people use when assessing rape allegations. These distortions result in the unjust exoneration of people we cannot conceive of as monstrous, while making it too easy to believe that some marginalized people could be rapists. I also argue that rape myths enable a novel kind of epistemic injustice. This injustice concerns how our assessments of trustworthiness and our assessments of plausibility interact. I argue that rape myths can result in runaway credibility deflations that can explain both why people fail to believe most women, and also why people may unjustly believe false allegations that white women have been raped by black men.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.710
Threshold uncertainty score0.999

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 studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.301
Teacher spread0.277 · 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