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Record W2246059939 · doi:10.1159/000381275

Children's Use of Speech and Repetition in Oral Storytelling: The Role of Cultural Patterning in Children's Retellings of First Nations Oral Narrative

2015· article· en· W2246059939 on OpenAlexaffabout
James Allen, Christopher E. Lalonde

Bibliographic record

VenueHuman Development · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsStorytellingNarrativeContext (archaeology)PsychologyRhetorical questionRepetition (rhetorical device)Narrative inquiryAffect (linguistics)Oral traditionSociologyDevelopmental psychologyPedagogyLinguisticsHistoryAnthropologyCommunication

Abstract

fetched live from OpenAlex

This paper presents a case study of a classroom of culturally diverse grade one students who participated in a First Nations cultural education program focused around traditional oral storytelling. The data reveal particular forms of narrative skills that these children were exploring in this context. Through a “verse analysis” of stories told to the children by a First Nations cultural educator and an analysis of the retellings of these stories by the children, we found that both the educator and the students employed a patterned use of speech and repetition to achieve particular rhetorical effects. We argue that examining children's participation in these particular forms of narrative practice provides evidence relevant to theories of cognitive development as a process of cultural participation, and it extends theoretical conceptions of children's narrative development to incorporate additional dimensions related to understandings of narrative form, evaluation, and the role of affect and the social context.

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)0.010
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.042
GPT teacher head0.294
Teacher spread0.252 · 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
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

Citations7
Published2015
Admission routes2
Has abstractyes

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