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Record W4386824505 · doi:10.3138/seminar.59.3.4

The Education of Desire: Unsettling Sexuality, Gender, and Racial Politics in Contemporary Medical Romance

2023· article· en· W4386824505 on OpenAlexvenueno aff
Katja Herges

Bibliographic record

VenueSeminar A Journal of Germanic Studies · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicGerman Colonialism and Identity Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRomanceAppropriationForegroundingGender studiesHuman sexualityColonialismQueerSociologyBourgeoisieGermanAestheticsPoliticsLiteratureRace (biology)ArtHistoryPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Medical romance features health care heroes and heroines in a central love story. This article analyzes two contemporary literary examples of the popular but neglected genre of German medical romance, Julya Rabinowich’s Herznovelle (2011) and Irena Brežná’s Schuppenhaut: Ein Liebesroman (2010). This article argues that medical romance performs agile cultural work that ambivalently locates discourses of desire, race, and gender within popular, literary, and medical cultures. Through a range of literary and autofictional strategies, both works reveal how medical romance can reflect and produce bourgeois sexuality and whiteness in contemporary culture. Foregrounding their narrators’ appropriation of colonial imagery, I show that Herznovelle and Schuppenhaut open up critical questions about approaches to decolonization in German studies and medical culture.

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)0.003
metaresearch head score (Gemma)0.004
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: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.050
Scholarly communication0.0060.005
Open science0.0000.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.124
GPT teacher head0.367
Teacher spread0.242 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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