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Record W4406781961 · doi:10.1111/bjdp.12547

Examining the influence of encoding and retrieval contexts on 2‐ to 4‐year‐olds' acquisition of nouns and verbs

2025· article· en· W4406781961 on OpenAlexafffund
Piper Swearengin, Patrick Mihalicz, Zoe Baker, Faith Perry, Susan A. Graham, Jane B. Childers

Bibliographic record

VenueBritish Journal of Developmental Psychology · 2025
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Children's Hospital FoundationChildren's Hospital Foundation
KeywordsNounVerbContext (archaeology)PsychologyObject (grammar)LinguisticsPerceptionWord (group theory)Context effectComputer scienceNatural language processingCognitive psychologyArtificial intelligence

Abstract

fetched live from OpenAlex

This study investigates whether the context in which a word is learnt affects noun and verb learning. There is mixed evidence in studies of noun learning, and no studies of background perceptual context in verb learning. Two-, three-, and four-year-olds (n = 162) saw a novel object moved in a novel way while hearing four novel words, either nouns or verbs. They were asked to generalize the word to a similar action or object shown in the same or different context. Results demonstrate that 2- and 3-year-olds were more accurate at test when learning nouns than verbs, demonstrating that verb learning is difficult; 4-year-olds were successful at learning both word types. For all ages, and both word types, context changes did not impact word learning. These results extend previous findings that context does not influence noun learning, while suggesting perceptual context may not play a major role in verb learning, which is a new finding.

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)0.001
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 score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.016
GPT teacher head0.308
Teacher spread0.292 · 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
Published2025
Admission routes2
Has abstractyes

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