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Children’s Literature in Education

2017· reference-entry· en· W2595773412 on OpenAlexaboutno aff
Kerry Mallan

Bibliographic record

VenueOxford Research Encyclopedia of Education · 2017
Typereference-entry
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsIronyPleasureStorytellingChinaReciprocalSociologyPolitical scienceHistoryGender studiesMedia studiesPsychologyPedagogyLiteratureLawArtNarrativeLinguistics

Abstract

fetched live from OpenAlex

Abstract Children’s literature is a dynamic entity in its own right that offers its readers many avenues for pleasure, reflection, and emotional engagement. As this article argues, its place in education was established centuries ago, but this association continues today in ways that are both similar and different from its beginnings. The irony of children’s literature is that, while it is ostensibly for children, it relies on adults for its existence. This reciprocal relationship between adult and child is, however, at the heart of education. Drawing on a range of scholars and children’s texts from Australia, Austria, Canada, China, Germany, Sweden, Switzerland, the United Kingdom, and the United States, this discussion canvasses some of the many ways in which children’s literature, and the research that it inspires, can be a productive and valuable asset to education, in that its imaginative storytelling is the means by which it brings the world into the classroom and takes the classroom out into the world.

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)0.007
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: Review · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.010
Science and technology studies0.0060.017
Scholarly communication0.0140.008
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0160.002

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 head0.034
GPT teacher head0.347
Teacher spread0.313 · 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
GenreReview

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

Citations139
Published2017
Admission routes1
Has abstractyes

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Same venueOxford Research Encyclopedia of EducationSame topicThemes in Literature AnalysisFrench-language works237,207