Writing and Deafness: State of the Evidence and Implications for Research and Practice
Bibliographic record
Abstract
Although reading and writing play equally important roles in the literacy development of deaf individuals, far more attention has been paid to reading than to writing in both research and practice. This is concerning as outcomes in writing have remained poor despite changes in communication philosophies (e.g., spoken and/or signed) and pedagogical approaches. Although there are indications of a positive shift as the context for deaf education has been transformed with advances in hearing technologies, challenges are ongoing. In order to better understand why deaf learners struggle to achieve age-appropriate outcomes in written language, the goal of this paper will be to take stock of the available research evidence in writing and deafness, and interpret it in light of both the Simple View of Writing (SVW), in which ideation or text generation is linked to oral language, and current models of the composing process. Based on this overview and analysis, implications and directions for future research and practice will be 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 | 0.030 | 0.113 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".