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Record W3198192097 · doi:10.1080/09669760.2021.1971949

Language expansion in Chinese parent–child mealtime conversations: across different conversational types and initiators

2021· article· en· W3198192097 on OpenAlexaboutno aff
Ling Sheng, Wenming Dong, Feifei Han, Shiming Tong, Jiangbo Hu

Bibliographic record

VenueInternational Journal of Early Years Education · 2021
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsnot available
FundersZhejiang Normal University
KeywordsPsychologyQuarter (Canadian coin)Developmental psychologyConversationVariation (astronomy)Language acquisitionLinguisticsCommunicationHistoryMathematics education

Abstract

fetched live from OpenAlex

This study examined the distribution of language expansion in parent–child (preschool aged) mealtime conversations in 30 Chinese middle-class families. The conversations were categorised into four types: contextualised & conflicted, contextualised & non-conflicted, decontextualised & conflicted, and decontextualised & non-conflicted. The language expansions were analysed using the systemic functional linguistic theory related to cohesive patterns in language expansion: elaborations, extensions, and enhancements. While the parents dominated the conversations generally, the children were active contributors, initiating over one-quarter of the conversations. Initiation had an impact on the distribution of the conversational types: the proportions of contextualised & non-conflicted conversations was significantly higher in child-initiated conversations. The contextualised & conflicted conversations accounted for a higher proportion in parent-initiated conversations. It was the conversational type rather than initiation, which had an effect on the distribution of language expansion patterns. The least occurring decontextualised & conflicted conversations generated the most extensions. The frequently appeared contextualised & non-conflicted conversations, however, produced the fewest expanded messages. The implications from the findings for promoting high-quality mealtime conversations conducive to children’s language learning are discussed.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.928

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.343
Teacher spread0.332 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

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