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Record W7125280327 · doi:10.30557/mt00349

Ragazzi che non possono crescere. Appunti su Peter Pan come Bildungsroman

2025· article· W7125280327 on OpenAlexaboutno aff
Simone Di Biasio

Bibliographic record

VenueMeTis - Mondi educativi Temi indagini suggestioni · 2025
Typearticle
Language
FieldArts and Humanities
TopicLiterature, Culture, and Aesthetics
Canadian institutionsnot available
Fundersnot available
KeywordsAdventureMythologyMeaning (existential)Context (archaeology)White (mutation)Bedroom

Abstract

fetched live from OpenAlex

In 1900, three children played surrounded by nature at Black Lake Cottage in Farnham, England, amid stories and panic-stricken metamorphoses planned by “Uncle Jim”. That experience gave rise to a bizarre book, The Boy Castaways of Black Lake Island, with photographs and short captions, the first work in which we glimpse the “shadow” of Peter Pan. The following year, James Matthew Barrie “Uncle Jim” published The Little White Bird, an anti-novel in which a six-day-old baby flies out of his bedroom window into Kensington Gardens. Thus began the adventure of one of the most successful characters in world literature, not only for children, with countless theatrical and film adaptations. Despite the subtitle - The Boy Who Wouldn't Grow Up - of the play that brought him resounding public success in 1904, Peter Pan is a powerful coming-of-age novel, with metaphors hidden beneath the images of shadows, islands and mythological ancestry with the god Pan. This contribution aims to investigate Barrie's most famous literary work in the context of the Bildungsroman, demonstrating how Peter Pan fully interprets the meaning of Bildung: growing up both as a rejection and as an inevitable, yet interpretable and questionable, destiny.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.509
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0060.001
Open science0.0020.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.013
GPT teacher head0.264
Teacher spread0.251 · 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; both teacher heads agree on what is shown here.

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
Published2025
Admission routes1
Has abstractyes

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