Qualitative differences between the joint effects of stimulus quality and word frequency in reading aloud and lexical decision: Extensions to Yap and Balota (2007).
Bibliographic record
Abstract
There have been multiple reports over the last 3 decades that stimulus quality and word frequency have additive effects on the time to make a lexical decision. However, it is surprising that there is only 1 published report to date that has investigated the joint effects of these two factors in the context of reading aloud, and the outcome of that study is ambiguous. The present study shows that these factors interact in the context of reading aloud and at the same time replicate the standard pattern reported for lexical decision. The main implication of these results is that lexical activation, at least as indexed by the effect of word frequency, does not unfold in a uniform way in the contexts reported here. The observed dissociation also implies, contrary to J. A. Fodor's (1983) view, that the mental lexicon is penetrable rather than encapsulated. The distinction between cascaded and thresholded processing offers one way to understand these and related results. A direction for further research is briefly noted.
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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 | 0.001 | 0.007 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".