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Record W2311353260 · doi:10.1080/15240657.2016.1135681

Transsexuality as Sinthome: Bracha L. Ettinger and the Other (Feminine) Sexual Difference

2016· article· en· W2311353260 on OpenAlexafffund
Sheila L. Cavanagh

Bibliographic record

VenueStudies in Gender and Sexuality · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicDiverse academic research themes
Canadian institutionsYork University
FundersSocial Sciences and Humanities Research Council of CanadaYork University
KeywordsSexual differenceTranssexualPsychoanalysisTransgenderRelation (database)NeurosisQueerPsychologySociologyComputer science

Abstract

fetched live from OpenAlex

This article uses Bracha L. Ettinger’s theory of the matrixial borderspace in relation to Jacques Lacan’s analytic of sexuation to argue that transsexuality isn’t reducible to psychosis. Rather, transsexuality taps into an Other (feminine) sexual difference that is subjectifying and can be understood in relation to Ettinger’s conception of metramorphosis and the matrixial. Transsexuality involves the somatization of the Other sexual difference and the creative use of this difference as sinthome. The sinthome of transsexuality can enable the subject to negotiate the aporia of sexual difference. I establish parallels between the (neurotic) hysteric and the transsexual to argue that transsexuality can be a subset of neurosis. The transsexual transition (which often involves Sex Reassignment Surgery) can be understood as a metramorphical becoming, a borderlinking enabling separation and distance in proximity. It is not as Catherine Millot (1990) contends an attempt to abolish the “nature” of the Real but rather a means to achieve a sinthomatic reknotting of the 3 Registers such that one’s relation to a parental image and to an Other’s primordial traces can be reconfigured.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.020
Scholarly communication0.0080.008
Open science0.0010.004
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0030.001

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 head0.432
GPT teacher head0.510
Teacher spread0.078 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations27
Published2016
Admission routes2
Has abstractyes

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