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Record W2811139869 · doi:10.1177/0142723718785013

Influences of number of adults and adult: child ratios on the quantity of adult language input across childcare settings

2018· article· en· W2811139869 on OpenAlexafffund
Mélanie Söderström, Elizabeth Grauer, Brenden Dufault, Karmen McDivitt

Bibliographic record

VenueFirst Language · 2018
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversity of Manitoba
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Manitoba
KeywordsHome languagePsychologyDevelopmental psychologyNaturalistic observationMedicineSocial psychologyPedagogy

Abstract

fetched live from OpenAlex

New approaches to examining the language environment are putting greater emphasis on the use of highly naturalistic audio recordings and questions about cross-cultural differences in children’s real-world language experiences. These new approaches and questions require careful examination of different kinds of variables that may influence children’s language experiences. The current study examines the influence of the number of adults and adult:child ratio on the number of words heard by young children across three childcare settings (home, home daycare and daycare centre). The home setting was characterized by a high number of one-on-one interactions, while children in daycare centres were exposed to larger numbers of adults present. While a linear relationship was found between the number/ratio of adults and words heard in the home setting, these relationships were more complex in daycare centres, and no relationships were found in home daycares.

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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.292
Teacher spread0.287 · 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

Citations41
Published2018
Admission routes2
Has abstractyes

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