American Sign Language syntactic and narrative comprehension in skilled and less skilled readers: Bilingual and bimodal evidence for the linguistic basis of reading
Bibliographic record
Abstract
ABSTRACT We tested the hypothesis that syntactic and narrative comprehension of a natural sign language can serve as the linguistic basis for skilled reading. Thirty-one adults who were deaf from birth and used American Sign Language (ASL) were classified as skilled or less skilled readers using an eighth-grade criterion. Proficiency with ASL syntax, and narrative comprehension of ASL and Manually Coded English (MCE) were measured in conjunction with variables including exposure to print, nonverbal IQ, and hearing and speech ability. Skilled readers showed high levels of ASL syntatic ability and narrative comprehension whereas less skilled readers did not. Regression analyses showed ASL syntactic ability to contribute unique variance in English reading performance when the effects of nonverbal IQ, exposure to print, and MCE comprehension were controlled. A reciprocal relationship between print exposure and sign language proficiency was further found. The results indicate that the linguistic basis of reading, and the reciprocal relationship between print exposure and “through the air” language, can be bimodal, as in being a sign language or a spoken language, and bilingual, as in being ASL and English.
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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 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".