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Record W2002507791 · doi:10.1037/a0025283

Is two a plural marker in early child language?

2011· article· en· W2002507791 on OpenAlexafffund
David Barner, Toni Lui, Jennifer A. Zapf

Bibliographic record

VenueDevelopmental Psychology · 2011
Typearticle
Languageen
FieldMathematics
TopicCognitive and developmental aspects of mathematical skills
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPluralNumeral systemLinguisticsPsychologyNounArabic numeralsArithmeticMathematicsPhilosophy

Abstract

fetched live from OpenAlex

Is two ever a plural marker in child language? By some accounts, children bootstrap the distinction between the words one and two by observing their use with singular-plural marking (one ball/two balls). Others argue that the numeral two marks plurality before children begin using numerals to denote precise quantities. We tested the relation between numerals and singular-plural marking in English-speaking 2- and 3-year-olds by asking them to label sets of objects. When children were not prompted to use numerals they hardly ever did so, although they did frequently use plural marking. Thus, it does not appear that children spontaneously use numerals like two as plural markers. Also, children who used numerals when labeling sets were significantly more likely to use a plural marker than children who did not use numerals, suggesting that most children view plural marking as obligatory when numerals are used, rather than viewing the 2 forms as alternative markers of plurality. Finally, two was no more likely than other numerals to be used with unmarked nouns (i.e., as an alternative to the plural), suggesting that it does not have a special status as a plural marker. We conclude that two is not a plural marker in early child language.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.275
Threshold uncertainty score0.999

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)0.0050.002

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 head0.058
GPT teacher head0.351
Teacher spread0.293 · 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; both teacher heads agree on what is shown here.

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

Citations16
Published2011
Admission routes2
Has abstractyes

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