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Record W2914700494 · doi:10.1386/jfs.6.3.319_1

Found in translation: Rethinking the relationship between fan translation groups and licensed distributors of anime and manga

2018· article· en· W2914700494 on OpenAlexaff
Alyssa Tremblay

Bibliographic record

VenueThe Journal of Fandom Studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicJapanese History and Culture
Canadian institutionsCarleton University
Fundersnot available
KeywordsAnimeTransformative learningAdvertisingTranslation (biology)Service (business)SociologyMedia studiesBusinessMarketingComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

This article examines contemporary systems, both legal and illegal, of anime and manga translation and distribution to English-speaking audiences. Rather than lumping fan translation in with practices such as fanart, cosplay or fan fiction, this article argues for a different understanding of the particularized labour of fan-operated anime and manga translation groups. Specifically, the continued existence of fan translation groups is considered indicative of consumers attempting to fill a gap in service not satisfied by licensed industry players – and fan translation itself as a practice born of consumer desire and perceived necessity, rather than creative or transformative expression.

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)0.003
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.755
Threshold uncertainty score0.638

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.157
GPT teacher head0.361
Teacher spread0.203 · 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 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

Citations2
Published2018
Admission routes1
Has abstractyes

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