Vietnamese compounds show an anti-frequency effect in visual lexical decision
Bibliographic record
Abstract
Although Vietnamese has a long history of linguistic research, as yet no psycholinguistic studies addressing lexical processing in this language have been carried out. This paper is the first to investigate lexical processing in Vietnamese, and this addresses the reading of Vietnamese bi-syllabic compound words. A large single-subject experiment with 20,000 words was complemented by a smaller multiple-subject experiment with 550 words. We report the novel finding of an inhibitory, anti-frequency effect of Vietnamese compounds’ constituents. We show that this anti-frequency effect is predicted by a computational model of lexical processing grounded in naive discrimination learning. We also show that predictors derived from this model provide a much better fit to the observed reaction times than traditional lexical-distributional predictors. Effects of the density of the compound graph, previously observed for English, were replicated for Vietnamese. Furthermore, tone diacritics were found to be important predictors of silent reading, providing further evidence for the role of phonology in reading.
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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 | 0.004 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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".