The cross-script length effect: Further evidence challenging PDP models of reading aloud.
Bibliographic record
Abstract
The interaction between length and lexical status is one of the key findings used in support of models of reading aloud that postulate a serial process in the orthography-to-phonology translation (B. S. Weekes, 1997). However, proponents of parallel models argue that this effect arises in peripheral visual or articulatory processes. The authors addressed this possibility using the special characteristics of the Serbian and Japanese writing systems. Experiment 1 examined length effects in Serbian when participants were biased to interpret phonologically bivalent stimuli in the alphabet in which they are words or in the alphabet in which they are nonwords (i.e., the visual characteristics of stimuli were held constant across lexical status). Experiment 2 examined length effects in Japanese kana when words were presented in the kana script in which they usually appear or in the script in which they do not normally appear (i.e., the phonological characteristics of stimuli were held constant across lexical status). Results in both cases showed a larger length effect when stimuli were treated as nonwords and thus offered strong support to models of reading aloud that postulate a serial component.
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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 | 0.005 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".