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Record W2076471598 · doi:10.1177/0142723705045678

Preschoolers’ talk about future situations

2005· article· en· W2076471598 on OpenAlexaff
Cristina M. Atance, Daniela K. O’Neill

Bibliographic record

VenueFirst Language · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCategorizationPsychologyTask (project management)Coding (social sciences)Developmental psychologyTest (biology)Language developmentCognitive psychologyComputer scienceArtificial intelligenceMathematicsStatistics

Abstract

fetched live from OpenAlex

We conducted 2 experiments that examined 3-year-olds’ ability to talk about future situations involving the self. In both experiments, children participated in a trip task. In this task, children were asked to choose various items that might be required on a trip, and to explain their choices verbally. A coding scheme that captured both the dimensions of futurity and uncertainty was developed to categorize children’s explanations. In addition, children were administered the Test of Early Language Development-2 (TELD-2) (Hresko, Reid & Hammill, 1991). Results from both experiments indicated that children’s language was beginning to reflect an ability to anticipate various situations involving the self that might arise during the course of a trip. The correlation between children’s scores on the trip task and their scores on the TELD-2 was positive, but not statistically significant. We discuss factors, other than general language ability, that may contribute to children’s talk, and thought, about the future.

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)0.006
metaresearch head score (Gemma)0.013
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 score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.008
GPT teacher head0.284
Teacher spread0.276 · 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

Citations45
Published2005
Admission routes1
Has abstractyes

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