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Record W4407994392 · doi:10.5771/9780810885172

Children's Literature and British Identity

2012· book· en· W4407994392 on OpenAlexaboutno aff
Rebecca Knuth

Bibliographic record

VenueRowman & Littlefield Publishers eBooks · 2012
Typebook
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsIdentity (music)GenealogyHistoryPsychologySociologyArtAesthetics

Abstract

fetched live from OpenAlex

For more than 250 years, English children’s literature has transmitted values to the next generation. The stories convey to children what they should identify with and aspire to, even as notions of “goodness” change over time. Through reading, children absorb an ethos of Englishness that grounds personal identity and underpins national consciousness. Such authors as Lewis Carroll, J. R. R. Tolkien, and J. K. Rowling have entertained, motivated, confronted social wrongs, and transmitted cultural mores in their works—functions previously associated with folklore. Their stories form a new folklore tradition that provides social glue and supports a love of England and English values. In Children’s Literature and British Identity: Imagining a People and a Nation, Rebecca Knuth follows the development of the genre, focusing on how stories inspire children to adhere to the morals of society. This book examines how this tradition came to fruition, exploring the works of several authors, including: Robert Baden-Powell Robert Ballantyne J. M. Barrie Enid Blyton Angela Brazil Frances Hodgson Burnett Randolph Caldecott Lewis Carroll Roald Dahl Daniel Defoe Charles Dickens Maria Edgeworth Kenneth Grahame Kate Greenaway G. A. Henty Thomas Hughes Charles Kingsley Rudyard Kipling C.S. Lewis A. A. Milne Hannah More E. Nesbit John Newbery George Orwell Beatrix Potter Arthur Ransome Frank Richards J. K. Rowling Anna Sewell Robert Louis Stevenson J. R. R. Tolkien P. L. Travers Sarah Trimmer Charlotte Yonge Evaluating the connection between children’s literature and the dissemination and formation of identity, this book will appeal to both general readers and academics who are interested in librarianship, English culture, and children’s literature.

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)0.002
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: Other · Consensus signal: Other
Teacher disagreement score0.256
Threshold uncertainty score0.509

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0090.009
Scholarly communication0.0100.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.001

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 head0.008
GPT teacher head0.192
Teacher spread0.184 · 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
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

Citations3
Published2012
Admission routes1
Has abstractyes

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Same venueRowman & Littlefield Publishers eBooksSame topicThemes in Literature AnalysisFrench-language works237,207