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Record W4206481127 · doi:10.1515/culture-2020-0141

A “Fabulous Monster” and a “Wonderful Boy:” Gender and the Elusive Victorian Child in the<i>Alice</i>Books and<i>Peter Pan</i>

2021· article· en· W4206481127 on OpenAlexaboutno aff
Friederike Frenzel

Bibliographic record

VenueOpen Cultural Studies · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsDreamWonderMonsterNarrativeQueerStorytellingHEROAlice (programming language)LiteraturePsychoanalysisArtArt historyHistoryPsychologyPhilosophyEpistemology

Abstract

fetched live from OpenAlex

Abstract Lewis Carroll’s “Alice in Wonderland” and “Through the Looking-Glass,” and J. M. Barrie’s “Peter Pan” are highly critiqued and explored works of British children literature. Both queer and hermeneutic readings allow approaches that intrinsically question gender dichotomies, providing tools to pick out underlying themes. Thus, focusing on the concepts of the “child hero” and the “genderless child” of Carroll’s and Barrie’s respective Victorian and Edwardian backgrounds, spatial – the dream worlds of the Wonder- and the Looking-Glass land, the colonized Island of Neverland – as well as temporal aspects – the linear, episodic quest of Alice, the immortal, cyclical existence of Peter – point to the subversive elements of play, memory, and narration in the texts. While Alice is bridging dream and reality in an oscillating, paradoxical act of self-aware transformation, Peter is otherworldly and inhuman himself, actively rejecting heteronormative standards and demands. Both are trespassers and assume roles, and confuse, adapt, and bend supposedly fixed rules. Their transgressions are subdued in the pretended ahistoricity of children’s storytelling, referring to the responsibility of adaptions to further expand the hermeneutical circle.

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)0.002
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 score0.138
Threshold uncertainty score0.274

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.035
Scholarly communication0.0070.004
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.040
GPT teacher head0.281
Teacher spread0.241 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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