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Record W1965732841 · doi:10.1017/s0142716413000258

Contextual effects on the conversations of mothers and their children with language impairment

2013· article· en· W1965732841 on OpenAlexafffund
Melanie Stich, Luigi Girolametto, Carla J. Johnson, Patricia L. Cleave, Xi Chen

Bibliographic record

VenueApplied Psycholinguistics · 2013
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsDalhousie UniversityUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyMean length of utteranceReading (process)Developmental psychologyMorphemeUtteranceConversationStyle (visual arts)Language developmentLanguage productionLinguisticsExpressive languageCommunicationCognition

Abstract

fetched live from OpenAlex

ABSTRACT Twenty-four mothers and their preschool children with language impairment participated in two 12-min sessions of toy play and book reading that were transcribed to yield maternal mean length of utterance in morphemes (MLU-m), type token ratio (TTR), and maternal interaction style (directive vs. responsive). Maternal MLU-m was significantly longer during book reading than during toy play, whereas TTR was similar across contexts. In contrast, children's MLU-m was similar across contexts, whereas TTR was higher during book reading. Mothers used an eliciting style characterized by more commands and questions during toy play than during book reading. Only maternal MLU-m predicted children's expressive language skills (i.e., a composite score of two standardized language tests). The implications include sampling both book reading and play interactions because they provide differential opportunities for conversation and language productivity.

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)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.006
GPT teacher head0.238
Teacher spread0.232 · 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 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

Citations15
Published2013
Admission routes2
Has abstractyes

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