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Record W4299641413 · doi:10.3138/jeunesse.6.2.72

How to Be Yourself: Ideological Interpellation, Weight Control, and YA Novels

2014· article· en· W4299641413 on OpenAlexvenueno aff
Dorothy Karlin

Bibliographic record

VenueJeunesse Young People Texts Cultures · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCharacter (mathematics)LiteratureIdeologyArtPhilosophyThe ThingPsychoanalysisAestheticsArt historyPoliticsPsychologyLawComputer sciencePolitical science

Abstract

fetched live from OpenAlex

This essay looks at images of disability in Shaun Tan’s The Lost Thing. The character of the lost thing, lost inside a world that clearly will not let it belong, represents the unrepresentable, while the boy narrator displays subtle depictions of cognitive difference. The lost thing’s body is incomprehensible for the very reason that it is so unlike the bodies of others. Although it may be tempting to read the boy narrator as dispassionate or as too emotionally detached because of his involvement with this uniform world, the protagonist gladly assists his new friend. As a different kind of thinker, the boy also does not quite fit in his world, even as he is not entirely separate from it.

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)0.004
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 score0.023
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0230.029
Scholarly communication0.0100.007
Open science0.0010.006
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0050.001

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 head0.011
GPT teacher head0.230
Teacher spread0.219 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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Same venueJeunesse Young People Texts CulturesSame topicThemes in Literature AnalysisFrench-language works237,207