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Record W2760217632 · doi:10.1017/s0142716417000236

Variations in phonological working memory: Linking early language experiences and language learning outcomes

2017· article· en· W2760217632 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueApplied Psycholinguistics · 2017
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsUniversité de MontréalMcGill University
Fundersnot available
KeywordsPsychologyLanguage developmentSecond-language attritionLanguage acquisitionCognitionDevelopmental linguisticsWorking memoryComprehension approachCognitive psychologyDevelopmental psychologySpeech perceptionSet (abstract data type)Language assessmentLinguisticsPerceptionLanguage educationComputer sciencePedagogyMathematics education

Abstract

fetched live from OpenAlex

ABSTRACT In order to build complex language from perceptual input, children must have access to a powerful information processing system that can analyze, store, and use regularities in the signal to which the child is exposed. In this article, we propose that one of the most important parts of this underlying machinery is the linked set of cognitive and language processing components that comprise the child's developing working memory (WM). To examine this hypothesis, we explore how variations in the timing, quality, and quantity of language input during the earliest stages of development are related to variations in WM, especially phonological WM (PWM), and in turn language learning outcomes. In order to tease apart the relationships between early language experience, WM, and language development, we review research findings from studies of groups of language learners who clearly differ with respect to these aspects of input. Specifically, we consider the development of PWM in children with delayed exposure to language, that is, children born profoundly deaf and exposed to oral language following cochlear implantation and internationally adopted children who have delayed exposed to the adoption language; children who experience impoverished language input, that is, children who experience early bouts of otitis media and signing deaf children born to nonsigning hearing parents; and children with enriched early language input, that is, simultaneous bilinguals and second language learners.

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.

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 score0.471
Threshold uncertainty score0.614

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.047
GPT teacher head0.369
Teacher spread0.322 · 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