Bibliographic record
Abstract
The present study supplements research on semantic effects in word processing by focusing on the role that meanings of morphemes play in recognition of complex words. We present an overview of behavioral effects of six semantic properties characterizing the emotional and sensory connotations of English compounds and their morphemes, as well as their semantic richness. Semantics of compounds affected latencies to those compounds, and semantics of morphemes affected latencies to those morphemes presented as isolated words. Yet semantics of morphemes had little bearing on recognition of compounds, with the exception of longer recognition times for compounds with emotionally negative morphemes (e.g., seasick). We interpret the data as evidence against obligatory decomposition and dual-route accounts of morphological processing and in favor of the naive discriminative learning account that posits independent, morphologically unmediated, and simultaneous access to all meanings activated by orthographic cues in the visual input. We discuss selectivity and division of attention as driving forces in complex word recognition.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".