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Record W2954166445 · doi:10.1558/jmbs.11126

“I have three years old”

2019· article· en· W2954166445 on OpenAlexaff
Elena Nicoladis

Bibliographic record

VenueJournal of Monolingual and Bilingual Speech · 2019
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRepresentation (politics)Mental lexiconVerbLinguisticsLexiconFixed pointMental representationExpression (computer science)Fixed effects modelPsychologyComputer scienceMathematicsCognitionStatisticsPanel dataProgramming language

Abstract

fetched live from OpenAlex

There is evidence that adults store fixed expressions as both units and compositionally in their mental lexicon. According to Usage-Based theories, children initially acquire memorized chunks of language (fixed expressions) and gradually abstract productive patterns (compositional representation). This study addresses whether a French-English bilingual child has compositional representation of fixed expressions using diary data on her use of fixed expressions requiring the verb to be in English and avoir ‘to have’ in French between the ages of 3;4 and 4;3. According to Usage-Based theories, children should learn these fixed expressions as fixed expressions and therefore show little cross-linguistic influence. However, from the earliest age under study, this child occasionally used the non-target verb, suggesting that her representation of these fixed expressions was already also compositional.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.288
Teacher spread0.274 · 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.

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

Citations3
Published2019
Admission routes1
Has abstractyes

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