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Record W2500281862 · doi:10.1177/1743872116661271

Relative Lust: Accidental Incest’s Affective and Legal Resonances

2016· article· en· W2500281862 on OpenAlexaff
Lara Karaian

Bibliographic record

VenueLaw Culture and the Humanities · 2016
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsCarleton University
Fundersnot available
KeywordsAffect theoryHuman sexualityKinshipSociologyPsychologyFetishismLustPornographyAffect (linguistics)SubjectivityQueerAccidentalSocial psychologyAestheticsPsychoanalysisCriminologyGender studiesEpistemologyArtPhilosophyCommunicationFeelingAnthropology

Abstract

fetched live from OpenAlex

This article explores the intimate relationship between the body, sexuality, technology, popular culture, and incest law. I examine the nature, meaning, and affective resonances of representations of consensual incest, “accidental incest,” and “technology facilitated accidental incest” in popular culture, pornography, and public service announcements. Drawing on a pastiche of affect theory; cultural and media studies theories of human-technological relations; queer, feminist and cultural posthumanist theories of embodiment, subjectivity and sexuality; and, Eve Sedgwick’s notion of a “reparative reading” I consider how these experiences and representations expand our emotional and erotic desires and alter our perceptions of our bodies’ parameters, their “proper” sexual objects and kinship relations, and their boundary violations. I argue that these affective residues pose a challenge to the “logic” underpinning the taboo’s intransigence, thus potentially contributing to the destigmatization and decriminalization of consensual adult incestuous relations.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.794
Threshold uncertainty score0.908

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 studies0.0000.002
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 head0.031
GPT teacher head0.303
Teacher spread0.273 · 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 designTheoretical or conceptual
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

Citations5
Published2016
Admission routes1
Has abstractyes

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