Preschool Children’s Narratives and Performance on the Peabody Individualized Achievement Test – Revised: Evidence of a Relation between Early Narrative and Later Mathematical Ability
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".