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Record W2035088287 · doi:10.1017/s0305000912000530

That's not what you said earlier: preschoolers expect partners to be referentially consistent

2013· article· en· W2035088287 on OpenAlexafffund
Susan A. Graham, Julie Sedivy, Melanie Khu

Bibliographic record

VenueJournal of Child Language · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsUniversity of Calgary
FundersSocial Sciences and Humanities Research Council of CanadaCanada Research Chairs
KeywordsPsychologyExpression (computer science)ReferentConversationObject (grammar)Developmental psychologyNonverbal communicationEye trackingCommunicationCognitive psychologyLinguistics

Abstract

fetched live from OpenAlex

In a conversation, adults expect speakers to be consistent in their use of a particular expression. We examine whether four-year-olds expect speakers to use consistent referential descriptions and whether these expectations are partner-specific. Using an eye-tracking paradigm, we presented four-year-olds with arrays of objects on a screen. During training, Experimenter 1 (E1) used a target expression to identify one object (i.e. "the spotted dog" to identify a dog that is both spotted and fluffy). Following training, either E1 or a new conversational partner (E2) presented children with test trials. Here, the target objects were referred to using either the original expression (e.g. "the spotted dog") or a new expression (e.g. "the fluffy dog"). Eye-movements indicated that preschoolers were quicker to identify the target referent when the original expression was used by the same speaker. This suggests that four-year-olds, like adults, expect communicative partners to adhere to referential pacts.

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)0.003
metaresearch head score (Gemma)0.008
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0000.001
Research integrity0.0020.001
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 head0.056
GPT teacher head0.297
Teacher spread0.240 · 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

Citations31
Published2013
Admission routes2
Has abstractyes

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