Accessing the meanings of sublexical forms during visual word recognition
Bibliographic record
Abstract
How are complex words recognized during the early moments of visual word recognition? What roles do full word and constituent frequency play in semantic processing? The present study addressed these questions by employing a word-picture relatedness task with brief stimuli presentations designed to tap the early mapping of orthographic input onto semantic representations. The main manipulation involved first presenting a picture depicting the target word’s constituent (200 ms), followed by the presentation of the target word (56 ms). We compared the rate of positive relatedness judgements elicited by picture-word pairs between suffixed (SKI-skier), pseudo-suffixed (MOTH-mother), and non-suffixed words (CAN-canoe). Results suggest that the “constituents” of all three word types are semantically accessed, although with a suffixed word advantage. Regression analyses did not corroborate behavioral findings as no full word and constituent frequency effects were obtained. We discuss the implications of these findings for models of the visual word recognition system.
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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 | 0.004 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".