The Varieties of Pathways to Dysfluent Reading
Bibliographic record
Abstract
The majority of work on the double-deficit hypothesis (DDH) of dyslexia has been done at the letter and word levels of reading. Key research questions addressed in this study are (a) do readers with different subtypes of dyslexia display differences in fluency at particular reading levels (e.g., letter, word, and connected text)? and (b) do children with dyslexia identified by either low-achievement or ability-achievement discrepancy criteria show similar differences when classified by the DDH? To address these questions, the authors assessed a sample of 158 children with severe reading impairments in second and third grades on an extensive battery and classified them into three reader subtypes using the DDH. The results demonstrated that the three DDH subtypes exhibited differences in fluency at different levels of reading (letter, word, and connected text), underscoring the separate reading profiles of these subtypes and the different possible routes to dysfluency in reading disabilities. Furthermore, the results suggest that the different patterns among DDH subtypes are primarily driven by the ability-achievement discrepancy group. The implications of these findings are discussed for intervention, reading theory, and a more refined understanding of heterogeneity.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".