The Role of Executive Functions in Lexical Processing During Reading Comprehension
Bibliographic record
Abstract
Abstract Robust relation has been revealed previously between the components of executive function (EF) and reading comprehension performance. However, the specific role of EF in the reading processes remains relatively underexplored. Within the framework of the lexical quality hypothesis (LQH), this study examined the contribution of EF to the lexical processing of words, and how this eventually supports reading comprehension. A total of 262 Grade 3 students in Hong Kong were assessed using multiple measures of EF, lexical processing skills (i.e. orthographic awareness, morphological awareness, and receptive vocabulary knowledge) and reading comprehension, respectively. Our findings indicate significant associations between EF and lexical processing skills, which, in turn, contributed to better reading comprehension. The results demonstrate how EF supports Chinese reading comprehension through the mediating effects of a reader's mental operation in obtaining meanings of individual words. The findings support to the notion that peripheral skills facilitate reading comprehension through more central skills.
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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".