Poor readers' retrieval mechanism: efficient access is not dependent on reading skill
Bibliographic record
Abstract
A substantial body of evidence points to a cue-based direct-access retrieval mechanism as a crucial component of skilled adult reading. We report two experiments aimed at examining whether poor readers are able to make use of the same retrieval mechanism. This is significant in light of findings that poor readers have difficulty retrieving linguistic information (e.g., Perfetti, 1985). Our experiments are based on a previous demonstration of direct-access retrieval in language processing, presented in McElree et al. (2003). Experiment 1 replicates the original result using an auditory implementation of the Speed-Accuracy Tradeoff (SAT) method. This finding represents a significant methodological advance, as it opens up the possibility of exploring retrieval speeds in non-reading populations. Experiment 2 provides evidence that poor readers do use a direct-access retrieval mechanism during listening comprehension, despite overall poorer accuracy and slower retrieval speeds relative to skilled readers. The findings are discussed with respect to hypotheses about the source of poor reading comprehension.
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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 | 0.002 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".