Silent Reading Fluency in Adult Literacy Learners: The Role of Phonemic Decoding and Speech Disfluencies
Bibliographic record
Abstract
INTRODUCTION: Challenges in reading and speech commonly co-occur. For example, adults and children with clinically elevated levels of speech disfluencies, indicating a speech fluency disorder, are more likely to have a reading disorder. METHOD: The aim of this study was to explore the connection between reading and speech difficulties in adult literacy learners (ALLs). We examined the relationship between phonemic decoding, speech disfluencies, and silent reading fluency in ALLs. Participants included 234 English-speaking ALLs enrolled in adult literacy programs in the USA and Canada. RESULTS: Taken together, results suggested that speech production ability mediated the relationship between reading and speech disfluencies. First, phonemic decoding skills positively predicted silent reading fluency, regardless of speech production ability. Second, in contrast to the first finding, higher speech disfluency rates were associated with stronger phonemic decoding only in ALLs with stronger speech production ability (i.e., ALLs with less disfluencies). Third, higher speech disfluency rates predicted lower silent reading fluency scores for ALLs with weaker speech production ability (i.e., ALLs with more disfluencies) but not for ALLs with stronger speech production ability. CONCLUSION: These findings point to the complex relationship between reading and speech abilities and underscore the importance of examining speech production skills in ALLs.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".