Evaluating Current Deficit Theories of Poor Reading: Role of Phonological Processing, Naming Speed, Balance Automaticity, Rapid Verbal Perception and Working Memory
Bibliographic record
Abstract
To clarify the nature of cognitive deficits experienced by poor readers, 9-10-yr.-old poor readers were matched against 9 chronological age and 9 younger reading age-matched controls screened and selected from regular classrooms. Poor readers performed significantly more poorly than chronological age-matched peers on digit naming speed, spoonerisms, and nonsense word reading. Poor readers were also significantly poorer than reading age-matched controls on nonword reading but were significantly better than reading age-matched controls on postural stability. Analyses of effect sizes were consistent with these findings, showing strong effects for digit naming speed, spoonerisms, and nonword reading. However, effect size analysis also suggested that poor readers experienced moderate difficulties with balance automatisation but did not show verbal speech perception deficits relative to either control
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".