Individual variability in the semantic processing of English compound words.
Bibliographic record
Abstract
Semantic transparency effects during compound word recognition provide critical insight into the organization of semantic knowledge and the nature of semantic processing. The past 25 years of psycholinguistic research on compound semantic transparency has produced discrepant effects, leaving the existence and nature of its influence unresolved. In the present study, we examined the influence of semantic transparency and individual reading experience on eye-movement behavior during sentence reading. Eye-movement data were collected from 138 non-college-bound 16- to 26-year-old speakers of English in a sentence-reading task representing a total of 455 different compound words. Measures of individual differences in reading experience were collected from the same participants and consisted of standardized assessments of exposure to printed materials, vocabulary size, and word recognition skill. Statistical analyses revealed facilitatory effects of both Modifier-Compound and Head-Compound transparency throughout the eye-movement record. Moreover, the study reports interactions between Head-Compound transparency and measures of reading experience. Readers with a small amount exposure to printed materials and a limited vocabulary size exhibited slower processing in late eye-movement measures when reading highly transparent compounds relative to opaque compounds. The opposite effect was observed for readers with a relatively large amount of exposure to printed materials and a relatively larger vocabulary size, such that highly transparent compounds facilitated lexical processing. To account for the results, the authors posit a trade-off between 2 cognitive mechanisms, which is modulated by individual reading experience; that is, the benefit of semantic coactivation of closely related concepts, and the cost of discriminating between those concepts. (PsycINFO Database Record
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".