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Record W4317241297 · doi:10.4324/9781003367253-5

Looking for Pei Lim's penis: melancholia, mimicry, pedagogy

2023· book-chapter· en· W4317241297 on OpenAlexaboutno aff
David Seitz

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsMimicryMelancholiaArtPenisVisual artsArt historyPsychologyAnatomyBiologyZoologySocial psychology

Abstract

fetched live from OpenAlex

This article considers the salience of Freud’s account of melancholia – one that points to the constitutive role of loss in subject formation – for understanding the racialization of queer sexuality and its mediation in pornography. Scholars have long and insightfully demonstrated the value of melancholia as an interpretive lens for making sense of the dynamics of racialization in the context of the contradictions of liberalism in the Global North. Taking cues from such work, I seek here to trace how pornography might stage returns to inaugural scenes of repudiated desire, and how it might proffer insight into the specificities of racial melancholia for queers. To illuminate the potential of constitutive loss for thinking about race in queer porn, I turn to the figure of Lim Pei-Hsien, an artist, activist, and porn star with a storied but rarely acknowledged history in Canadian LGBTQ, AIDS, and anti-racist circles. I argue that sustained engagement with Lim’s work positions him as a profoundly and perhaps instructively melancholic figure, one who might productively inform thinking on race, queerness, and pornography, particularly when read through a psychoanalytic lens.

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)0.001
metaresearch head score (Gemma)0.002
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: Other · Consensus signal: Other
Teacher disagreement score0.005
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0050.016
Scholarly communication0.0040.005
Open science0.0000.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.080
GPT teacher head0.301
Teacher spread0.220 · 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
GenreOther

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

Citations0
Published2023
Admission routes1
Has abstractyes

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