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Record W3093232320 · doi:10.21900/j.jams.v1.231

Desiring Futures

2020· article· en· W3093232320 on OpenAlexaff
Leo Chu

Bibliographic record

VenueThe Journal of Anime and Manga Studies · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicUtopian, Dystopian, and Speculative Fiction
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDystopiaSubversionDepictionUtopiaSociologyAestheticsNarrativePoliticsVariety (cybernetics)Futures contractCriticismEpistemologyLiteraturePhilosophyArtLawPolitical scienceComputer science

Abstract

fetched live from OpenAlex

In this paper, I analyze the animated television series Puella Magi Madoka Magica based on a variety of literary critical methods: neo-noir criticism, feminist epistemology and studies of technoscience, and discussion of utopia/dystopia imagination. My focus is on the depiction of desire and hope, as two interconnected but potentially conflicting concepts, in Madoka Magica which presents different philosophical edifices related to them as one central narrative tension. On the other hand, the feminist methods I utilize will demonstrate how the “genre subversion” the series introduce can be read alongside with not only magical girls’ struggle against their fates in the fiction but the real power structures and asymmetries in (post-)modern society. By highlighting the difficulties to resist a future and ethics imposed from the standpoint of dominant social groups as well as the attempt to solve such impasse by the series, the paper argues that Madoka Magica, while not committing itself to the creation of a radical alternative to the existent political or economic systems, has nonetheless affirmed the possibility and importance to have hope for futures that are yet to be imagined.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0080.015
Scholarly communication0.0060.009
Open science0.0010.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0200.003

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 head0.167
GPT teacher head0.273
Teacher spread0.106 · 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 designTheoretical or conceptual
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
Published2020
Admission routes1
Has abstractyes

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