Specificity, Co-Occurrence, and Growth: Math and Reading Skill Development in Children With Learning Disabilities
Why this work is in the frame
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Bibliographic record
Abstract
Learning disabilities are challenging to characterize because they evolve throughout development, frequently co-occur, and have varying domain specificity. Addressing these challenges, we analyzed longitudinal patterns of growth, co-occurrence, and specificity manifesting in the math and reading skills of children with and without learning disabilities. With a sample of 498 Grade 1 U.S. children followed for 5 years, we used linear mixed-effects models to explore group-level differences among children with math disability (MD), reading disability (RD), co-occurring disability, and no disability. Findings revealed: Math and reading trajectories of children with learning disabilities parallel those of children without disabilities. Skill growth slows over time, regardless of skill level, suggesting disability-related impairments will not resolve without intervention. Impairment levels and growth trajectories of children with co-occurring disabilities match the within-domain patterns of children with isolated disabilities, supporting a longitudinally maintained additive model of co-occurrence. MD and RD show varying specificity. MD impairments are domain-specific and become more pronounced over time. RD impairments impact both domains early, become more domain-specific over time, but maintain curriculum-contingent math deficits. Findings suggest early math intervention should balance linguistic and conceptual support, as the source of a child's math difficulties may not be clear until well into elementary school.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it