Phonological Facilitation from Pictures in a Word Association Task: Evidence for Routine Cascaded Processing in Spoken Word Production
Bibliographic record
Abstract
While most authors now agree that the language production system is in principle cascaded, the strength with which cascaded lemma-to-phoneme activation typically occurs is debated. Picture naming has been shown to be facilitated by phonologically related distractor pictures, but no such facilitation from pictures has been shown for word reading. Picture-picture paradigms have recently been suggested to represent an attentionally facilitated and unusually strong case of cascaded phonological facilitation, not typical of a more general weakly cascaded production system. We used a novel procedure based on picture-word interference paradigms, where participants made speeded verbal free association responses to presented words, with irrelevant picture distractors that were phonologically related to their predicted high-associate responses. Phonological facilitation effects from related picture names were observed on free associate verbal production latencies. These findings represent a far more general demonstration of routine cascaded language production and suggest that the strength and extent of cascaded activation is more substantial than that suggested by traditional picture-word paradigms.
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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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".