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Record W4311506759 · doi:10.21900/j.jams.v3.868

Prefiguring the Otokonoko Genre

2022· article· en· W4311506759 on OpenAlexaff
Riley Hannah Lewicki

Bibliographic record

VenueThe Journal of Anime and Manga Studies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicJapanese History and Culture
Canadian institutionsMcGill University
Fundersnot available
KeywordsAnimeQueerAppealGirlPopularityLiteraturePopular culturePopular fictionArtSubversionHistorySociologyGender studiesPsychologyPhilosophyLinguistics

Abstract

fetched live from OpenAlex

This article examines two manga, Stop!! Hibari-Kun! and No Bra, which prefigure the increasingly popular anime and manga genre of "Otokonoko" from a queer studies perspective. Otokonoko is a term which translate to “boy-girl”, “boy-daughter”, or “boy-princess” and is often translated into English as “cross-dresser”. The genre emerged in the early 2000s and has since become a popular point of reference and conversation both within and outside of anime and manga communities. Both the genre, and its titular characters have become iconic within both Japanese and Western online culture. As with most genres, the otokonoko genre is trope heavy, so it was decided to look at works that prefigure the genre to better understand the appeal without the weight of the traditions of the genre weighing too heavily on the content. Both Stop!! Hibari-Kun! and No Bra follow the story of a boy who becomes increasingly attracted to a gender ambiguous character assigned male at birth, but who appears female to most. Both manga are centrally about this conflict between the love interests’ perceived maleness and the protagonists perceived heterosexuality. The article analyses the appeal of each work to both male and trans feminine readers, because what would later become the otokonoko genre is written and read by both male and trans feminine readers. It also argues that these manga offer something unique from Western depictions of transgender lives, based on the popularity of manga and anime among Western trans feminine readers.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.523
Threshold uncertainty score0.998

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 studies0.0030.000
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 head0.050
GPT teacher head0.309
Teacher spread0.260 · 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.

Study designQualitative
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

Citations1
Published2022
Admission routes1
Has abstractyes

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