Reading is in the eye of the beholder: eye movements and early word processes in deaf readers of French
Bibliographic record
Abstract
For the present dissertation, three studies were conducted to investigate various aspects of reading in severely to profoundly deaf individuals who use Quebec Sign Language as their main mode of communication and who were categorized as skilled or less skilled readers. A group of skilled hearing readers also participated so that their results could be compared to existing literature. Two studies investigated the use of orthographic and phonological codes during early French word processing, with a masked primed lexical decision task (Study 1) and with the observation of eye movements (Study 3). The second study served as a bridge between the first and the third studies. The participants' eye movements were recorded to determine their eye movement characteristics, such as their reading speed and the size of their perceptual and word identification spans. The results of the first and third studies converged to show that deaf readers, skilled and less skilled, process orthographic (Studies 1 & 3) and phonological (Study 1) codes very early during word processing. Importantly, skilled and less skilled deaf readers did not differ in the way they encode words relative to the control group of hearing readers. The observation of the participants' eye movements in the second study revealed that reading-level, not hearing status (hearing or deaf), was the main factor determining the characteristics of the participants' eye movements (such as reading speed, size of the word identification span, etc). However, hearing status was a determining factor in the size of the perceptual span of skilled deaf readers, which, unexpectedly, was wider than that of skilled hearing readers. An o
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".