Examining the validity of three methods of measuring pre-readers’ knowledge of storybook events
Bibliographic record
Abstract
Planning intervention for narrative comprehension deficits requires a thorough understanding of a child’s skill in all component domains. The purpose of this study was to examine the validity of three methods of measuring pre-readers’ event knowledge, an important predictor of story comprehension. Thirty-eight typically developing children (12 males; 26 females) between the ages of 30–59 months ( M = 42.05 SD = 7.62) completed three measures – verbal account, enactment, picture-sequencing – that tapped their knowledge of two different events before listening to stories based on each of those events and completing story comprehension tasks. Scores for verbal account and enactment, but not for picture sequencing, (1) were moderately correlated with comprehension scores for the corresponding story; (2) reflected differential knowledge of the two events, though not in the expected direction; (3) were moderately correlated with one another in the case of each story. In general measures for the same event were more highly correlated with one another than with measures of the other event. Overall, results suggest that verbal account and enactment may yield information useful for clinicians planning intervention for children with narrative comprehension deficits.
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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 | 0.010 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".