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Record W2098475450 · doi:10.1017/s0305000910000127

Early verb learning in 20-month-old Japanese-speaking children

2010· article· en· W2098475450 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

VenueJournal of Child Language · 2010
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsMcGill University
Fundersnot available
KeywordsVerbSalience (neuroscience)SentencePsychologyTask (project management)Action (physics)CognitionPerceptionLinguisticsCognitive psychologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

The present study investigated whether children's representations of morphosyntactic information are abstract enough to guide early verb learning. Using an infant-controlled habituation paradigm with a switch design, Japanese-speaking children aged 1 ; 8 were habituated to two different events in which an object was engaging in an action. Each event was paired with a novel word embedded in a single intransitive verb sentence frame. The results indicated that only 40% of the children were able to map a novel verb onto the action when the mapping task was complex. However, by simplifying the mapping task, 88% of the children succeeded in verb-action mapping. There were no differences in perceptual salience between the agent and action switches in the task. These results provide strong evidence that Japanese-speaking children aged 1 ; 8 are able to use an intransitive verb sentence frame to guide early verb learning unless the mapping task consumes too much of their cognitive resources.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.267
Threshold uncertainty score0.998

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 integrity0.0000.001
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 head0.005
GPT teacher head0.253
Teacher spread0.248 · 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