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Record W4413121559 · doi:10.1177/14687984251367651

Storying worlds: Thinking and doing otherwise in young children’s story pedagogy

2025· article· en· W4413121559 on OpenAlexafffundabout
Kimberly Lenters, Anne Cloarec, Ronna Mosher

Bibliographic record

VenueJournal of Early Childhood Literacy · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsBP (Canada)University of Calgary
FundersSocial Sciences and Humanities Research Council of CanadaCanada Research Chairs
KeywordsNarrativeConversationAestheticsSociologyPedagogyVisual artsLiteraturePsychologyArtCommunication

Abstract

fetched live from OpenAlex

Children's storied play, or in other words, their fictive world-building, has much to teach us with regard to understanding story and how story pedagogy might be otherwise shaped in curricular spaces. In this article, we explore this proposition by drawing on interconnected and entangled moments of children's outdoor storied play in a Canadian first-grade class. By mapping the children's movements within three storied-play encounters, we animate how what could appear as the most ordinary and mundane ways of composing story in outdoor, open-ended and make-believe play, offers a lively form of protestation to the predominant Western narrative paradigm of beginning-middle-end story structure. Bringing the three moments into conversation with literary theorist Marielle Macé's concept of narrative stylization, we attend to ways story lives and grows within children's storied and playful worldbuilding. Ultimately, we argue that limiting instructional methods to that which is centred around the objectification and rationalization of storying (i.e., typical beginning-middle-end story structure) can displace other pedagogical directions that recognize and extend the myriad ways in which stories are made, learned, and understood. We conclude the article with an exploration of how educators might promote and build upon the narrative stylizations - fiction-in-the-doing - that children are always already engaging in their storied play.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.749
Threshold uncertainty score0.807

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.246
Teacher spread0.242 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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 routes3
Has abstractyes

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