How Do Deaf Signers of LSQ and Their Teachers Construct the Meaning of a Written Text?
Bibliographic record
Abstract
Many studies have investigated why learning to read is so problematic for deaf individuals. However, we still know very little about how to teach reading to signing students. In this article, we report on an exploratory qualitative study of deaf LSQ (Langue des signes québécoise) signers learning to read with two teachers, in an effort to better understand what strategies might be most useful in constructing the meaning of a text. By videotaping reading sessions between each teacher and student, then conducting recall interviews, we found that both students and teachers used a number of strategies to construct meaning. The list of strategies observed was categorized as word attack or global meaning types. Developing readers showed different patterns of strategy use, with more global meaning strategies being used by the more independent reader. We also found that the deaf teacher and hearing teacher had different patterns of strategy use, although both favored global meaning types. Finally, our findings indicate that both teachers adapted their strategy use to the needs of the students, but with a different focus. Namely, the deaf teacher used more global meaning strategies with the weaker reader and less with the more independent reader, whereas the hearing teacher showed the opposite pattern.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".