The Influence of Diglossia on Different Types of Phonological Abilities in Arabic
Bibliographic record
Abstract
The present study examined the impact of diglossia, a characteristic of the Arabic language, on the developmentof phonological abilities in the spoken and the literary language forms. Participants were 571 children from 10grade levels (1-7, 9, 11 and 12), which were recruited from 10 schools by taking into account two importantfactors: the accent factor (Bedouins, Druze and Arabs) and the geographical factor (south, Haifa, center andnorth). All participant were administered phonemic segmentation and phonemic deletion tasks, each comprisedof two types of stimulus: spoken and literary words. The results indicated an opposite effects of the stimuluswhere in the phonemic segmentation tasks, an advantage was found for the spoken stimulus over the literary andin the phonemic deletion task, the advantage was recorded in the literary stimulus. In addition, a significant maineffect of grade was found for both tasks. An interaction between grade and the type of stimulus was observedonly in the phonemic deletion task. These differences between the two tasks may suggest that they are processeddifferently via the auditory and the visual modality. In addition, our findings provide evidence concerns thedevelopmental capacity of phonemic awareness. The results, as a whole, support the notion that the effect oflexical distance on phonological awareness depends on modes of stimulus presentation.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".