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Record W2490844379 · doi:10.1057/9781137356000_1

Introduction: The Compulsion to Repeat

2014· book-chapter· en· W2490844379 on OpenAlexaff
Mavis Reimer, Nyala Ali, Deanna England, Melanie Dennis Unrau

Bibliographic record

VenuePalgrave Macmillan UK eBooks · 2014
Typebook-chapter
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsScholarshipNarrativeLiteraturePublishingHistoryCriticismLiterary criticismArtLawPolitical science

Abstract

fetched live from OpenAlex

There is a curious gap in the scholarship on texts for young people: while series fiction has been an important stream of publishing for children and adolescents at least since the last decades of the nineteenth century, 1 the scholarship on these texts has not been central to the development of theories on and criticism of texts for young people. The focus of scholarship is much more likely to be on stand-alone, high-quality texts of literary fiction. Kenneth Grahame’s The Wind in the Willows (1908), for example, has occupied critics in the field far more often and more significantly than all of the 46 popular novels about schoolgirls with similar plots that were published by Grahame’s contemporary, Angela Brazil (beginning in 1904 with A Terrible Tomboy) . Literary fiction such as Grahame’s tends to be defined in terms of its singularity — the unique voice of the narrator, unusual resolutions to narrative dilemmas, intricate formal designs, and complicated themes -often specifically as distinct from the formulaic patterns of series fiction. Yet, curiously, scholars typically use examples from literary fiction to illustrate the common characteristics of books directed to young readers: it was Grahame’s book, and not Brazil’s books, that appeared in the Children’s Literature Association’s list Touchstones as one of the “distinguished children’s books” the study of which “will allow us to better understand children’s literature in general,” according to Perry Nodelman, who chaired the committee that produced the list (2). These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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)0.003
metaresearch head score (Gemma)0.017
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.136
Threshold uncertainty score0.456

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0070.009
Open science0.0020.006
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.1360.106

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 head0.015
GPT teacher head0.212
Teacher spread0.197 · 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
Published2014
Admission routes1
Has abstractyes

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Same venuePalgrave Macmillan UK eBooksSame topicThemes in Literature AnalysisFrench-language works237,207