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Record W2037854888 · doi:10.1080/15248372.2012.728544

Now You Hear It: Fourteen-Month-Olds Succeed at Learning Minimal Pairs in Stressed Syllables

2012· article· en· W2037854888 on OpenAlexaff
Stephanie L. Archer, Jennifer Ference, Suzanne Curtin

Bibliographic record

VenueJournal of Cognition and Development · 2012
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversity of Calgary
FundersSanten
KeywordsSyllablePsychologyWord (group theory)Object (grammar)Word learningAssociative learningTask (project management)Associative propertyCommunicationLinguisticsCognitive psychologySpeech recognitionComputer scienceMathematicsVocabulary

Abstract

fetched live from OpenAlex

We examined whether 14-month-olds learn the mapping between a novel word and object in an associative-learning task when the forms differ minimally in only one segment where the crucial difference occurs in a stressed syllable. Fifty infants were presented with novel word–object pairings. Infants in one group heard the minimal difference in an initially stressed syllable, and the other group heard the minimal difference in a medially stressed syllable. Only those infants who were taught the medially stressed minimal pair detected a mismatch in the word–object pairing. These results demonstrate that 14-month-olds can succeed at minimal pair word learning when the critical information is presented in a stressed syllable, but importantly, only when particular acoustic cues are highlighted by syllable position—in this case, the medial position.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.025
GPT teacher head0.287
Teacher spread0.262 · 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

Citations12
Published2012
Admission routes1
Has abstractyes

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