Investigating the Double-Deficit Hypothesis in Greek
Bibliographic record
Abstract
This study examined longitudinally the double-deficit hypothesis in Greek, an orthographically consistent language, following a group of children from kindergarten to Grade 2. Four groups were formed on the basis of two composite scores of phonological and naming-speed criterion measures: a double-deficit group (DD; n = 17), a phonological deficit group (PD; n = 33), a naming deficit group (ND; n = 33), and a control group exhibiting no deficits (CnD; n = 159). The four groups were identified in Grade 1, and they were compared retrospectively in kindergarten only on the criterion measures, and in Grades 1 and 2 on measures of word-reading fluency and accuracy, orthographic processing, and passage comprehension. The effects of verbal and nonverbal ability, age, gender, and parental education were controlled among the groups. Results showed that the DD group exhibited greater dysfunction in reading and orthographic processing compared to the single-deficit and CnD groups. Also, although the three deficit groups were not easily differentiated in kindergarten, their differences were maximized in Grade 1 and retained in Grade 2. The type and severity of reading deficits found in the ND group were mostly associated with naming speed at both the word- and text-reading levels, deficits that persisted across development. The PD group showed mostly deficient orthographic and poor decoding skills that improved across development. Implications of the findings for the double-deficit hypothesis in languages with transparent orthographies are discussed.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".