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Record W4285370181 · doi:10.1386/qsmpc_00062_1

Resurrecting ParaNorman: Ghosts and gays in the New Queer Cartoon

2021· article· en· W4285370181 on OpenAlexaff
Derritt Mason

Bibliographic record

VenueQueer Studies in Media & Popular Culture · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicMedia, Gender, and Advertising
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsQueerMainstreamCharacter (mathematics)Representation (politics)AestheticsArtPoint (geometry)Visual artsSociologyMedia studiesGender studiesPoliticsPolitical scienceLaw

Abstract

fetched live from OpenAlex

When the Oscar-nominated, stop-motion animated film ParaNorman was released in August 2012, critics made much ado about the supporting character named Mitch: a dopey, beefy jock perceived to be the first openly gay character in a mainstream American children’s animated movie. As queer representation in children’s animated media continues to expand – as seen, for example, in Netflix’s 2021 film The Mitchells vs. the Machines, which features an openly queer protagonist – this article argues that Mitch’s now decade-old legacy is worth revisiting. Drawing on Noreen Giffney’s concept of the ‘New Queer Cartoon’, ParaNorman, I claim, marks a crucial turning point in children’s animated media. The film represents a collision between the latently and openly queer – it nods to the coded queer signifiers of past films while simultaneously making possible the gradual increase in visible queer representation that has taken place since its release.

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)0.003
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 score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0080.012
Scholarly communication0.0050.005
Open science0.0000.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.083
GPT teacher head0.382
Teacher spread0.299 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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