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Record W4415788777 · doi:10.1111/japp.70058

Tracking the Epistemic Harms of Marital Rape: The Case for Experiential Injustice

2025· article· en· W4415788777 on OpenAlex
Sushruth Ravish, Ritu Sharma

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

VenueJournal of Applied Philosophy · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicFeminist Epistemology and Gender Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHarmInjusticeExperiential learningEconomic JusticeTracking (education)Experiential knowledge

Abstract

fetched live from OpenAlex

ABSTRACT Empirical studies suggest that rape in marriages continues to be treated as a less severe crime than other forms of rape. Although the psychological and legal dimensions of marital rape have received some attention, its epistemic harms remain under‐theorised. This article argues that these harms are not exhausted by hermeneutical injustice, where victims lack the conceptual resources to identify or articulate their experience as rape. We introduce the concept of experiential injustice to capture a deeper epistemic harm in which victims, shaped by trauma or internalised oppression, lose evaluative grip on their own experience. Drawing on victims' testimonies, we show how marital rape can erode epistemic self‐trust and diminish the capacity to register harm as experientially significant. These harms resist easy remediation and call for a broader framework to understand how epistemic injustice occurs in the contexts of marital rape. Recognising these layered epistemic harms is crucial for legal and social reforms addressing marital rape.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.649
Threshold uncertainty score0.815

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 studies0.0010.001
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 head0.038
GPT teacher head0.339
Teacher spread0.301 · 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