Word-Level Stress Is to Decoding as Phrase-Level Stress Is to Reading Comprehension: A Study of Prosodic Influence in Children’s Reading Development
Bibliographic record
Abstract
This study aims to determine how the use of prosody in spoken language can effect reading development and later, reading ability as an adult. Research shows that individuals who can identify which syllables or words are emphasized within a phrase also have more advanced decoding abilities (i.e. are more proficient at translating letters into speech sounds) and have more advanced reading comprehension. To date, there has been little research examining the precise method by which this awareness of emphasis or “stress” at the word-level and the phrase-level uniquely contribute to reading ability. In this study, I predict that adults’ word-level stress awareness will be more strongly predictive of their word decoding ability than their reading comprehension. I also postulate that adult’s awareness of stress at the phrase-level will be more predictive of their reading comprehension than decoding, when word-level stress sensitivity is removed from the equation. Eighty students from Queen’s University were recruited to participate in two 60-minute interview sessions, during which completed a battery of reading and executive functioning tasks. Multiple regression analyses will be conducted to evaluate the relationship between the measures of interest. The results from this study will benefit elementary school teachers, speech-language pathologists and others working towards providing children with a solid foundation in the spoken language from which their literacy skills can grow. These results may also have important implications for the development of educational programs for individuals with specific reading impairments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".