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Record W2105610385 · doi:10.1177/0142723704043529

Preschool Children’s Narratives and Performance on the Peabody Individualized Achievement Test – Revised: Evidence of a Relation between Early Narrative and Later Mathematical Ability

2004· article· en· W2105610385 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFirst Language · 2004
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNarrativeSpellingDevelopmental psychologyPsychologyAchievement testAcademic achievementTest (biology)Perspective (graphical)Reading (process)Reading comprehensionStandardized testRelation (database)ComprehensionMathematics educationLinguisticsMathematics

Abstract

fetched live from OpenAlex

In this study, different measures derived from 41 3- to 4-year-old children’s selfgenerated picture-book narratives and their performance on a general measure of language development (TELD-2, Hresko, Reid & Hammill, 1991) were evaluated with respect to their possible predictive relation two years later with 5 areas of academic achievement (General information, Reading recognition, Reading comprehension, Math, Spelling) assessed using the Peabody Individualized Achievement Test – Revised (PIAT-R, Markwardt, 1998). Children’s TELD-2 scores were significantly predictive of their General information scores. The narrative measures of conjunction use, event content, perspective shift, and mental state reference were significantly predictive of later Math scores. Post-hocanalyses revealed that, for the same children, the observed relations with Math achievement did not arise with nonspontaneous adult-prompted narrations.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.375
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.019
GPT teacher head0.297
Teacher spread0.278 · 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