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Record W2794006604 · doi:10.1080/15475441.2018.1427589

The Genetic and Environmental Etiology of the Association between Vocabulary and Syntax in First Grade

2018· article· en· W2794006604 on OpenAlexafffund
Catherine Mimeau, Ginette Dionne, Bei Feng, Mara Brendgen, Frank Vitaro, Richard E. Tremblay, Michel Boivin

Bibliographic record

VenueLanguage Learning and Development · 2018
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversité de MontréalUniversité du Québec à MontréalUniversité Laval
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health ResearchCanadian Language and Literacy Research NetworkFonds de Recherche du Québec-Société et CultureCanada Research ChairsCanadian Institute for Advanced Research
KeywordsSyntaxVocabularyAssociation (psychology)PsychologyPopulationVocabulary developmentLinguisticsDevelopmental psychologyComputer scienceNatural language processingDemographySociology

Abstract

fetched live from OpenAlex

This twin study examined the genetic and environmental etiology of vocabulary, syntax, and their association in first graders. French-speaking same-sex twins (n = 555) completed two vocabulary tests, and two scores of syntax were calculated from their spontaneous speech at 7 years of age. Multivariate latent factor genetic analyses showed that lexical skills were influenced mainly by the environment shared between the twins, whereas syntactic skills were influenced exclusively by genes and unique environment. Moreover, the moderate association between vocabulary and syntax was mostly due to common genetic factors. These novel findings may be attributable to the use of latent factors and the population studied. More research is needed to determine the specific factors involved in lexical and syntactic skills at this developmental period.

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)0.006
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 score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.235
Teacher spread0.229 · 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

Citations2
Published2018
Admission routes2
Has abstractyes

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