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Record W2427014839 · doi:10.23889/suthesis.42979

(De)monstration: Interpreting the monsters of English children's literature.

2006· dissertation· en· W2427014839 on OpenAlexaboutno aff
Jonathan Padley

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)AdventureHistoryPerformance artLiteratureArtPsychologyArt historyPsychoanalysis

Abstract

fetched live from OpenAlex

This thesis is intended to document and explain the peculiarly high incidence of monsters in English children’s literature, where monsters are understood in the term’s full etymological sense as things which demonstrate through disturbance. In this context, monsters are frequently young people themselves; the youthful protagonists of children’s literature. Their demonstrative operation typically functions not only as an overt or covert tool by which to educate children’s literature’s implied child audience, but also as a wider indicator - demonstrator - of adult appreciations of and arguments over children and how children should be permitted to grow. In this latter role especially, children are rendered truly monstrous as alienated and problematic tokens in adult cultural arguments. They can fast become such efficient demonstrators of adult crises that their very presence engenders all the notions of unacceptability with which monsters are characteristically associated. The chronological range of this thesis’ study is the eighteenth-century to the present. From this period, the following children’s authors, children’s books, and series of children’s books have been examined in detail: • Thomas Day: Sandford and Merton • Anna Laetitia Barbauld: Lessons for Children and Hymns in Prose for Children • Sarah Trimmer: Fabulous Histories • Mary Martha Sherwood: The Fairchild Family • Charles Kingsley: The Water-Babies • Lewis Carroll: Alice’s Adventures in Wonderland and Through the Looking-Glass • George MacDonald: At the Back of the North Wind • J.M. Barrie: Peter Pan in Kensington Gardens, Peter Pan, and Peter and Wendy • C.S. Lewis: The Chronicles of Narnia (The Lion, the Witch & the Wardrobe, Prince Caspian, The Voyage of the Dawn Treader, and The Last Battle) • J.K. Rowling: Harry Potter {The Philosopher’s Stone, The Chamber of Secrets, The Prisoner of Azkaban, The Goblet of Fire, The Order of the Phoenix, and The HalfBlood Prince). The theoretical notions of monsters and monstrosity that are used to discuss these texts draw principally on the writings on the sublime by Edmund Burke and Immanuel Kant, the uncanny by Sigmund Freud, and the fantastic by Tzvetan Todorov.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0070.011
Scholarly communication0.0070.006
Open science0.0010.003
Research integrity0.0010.003
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 head0.004
GPT teacher head0.208
Teacher spread0.204 · 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 designQualitative
Domainnot available
GenreOther

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
Published2006
Admission routes1
Has abstractyes

Explore more

Same topicThemes in Literature AnalysisFrench-language works237,207