Second language effects on ambiguity resolution in the first language
Bibliographic record
Abstract
The processing of homonyms is complex considering homonyms have many lexical properties. For instance, train contains semantic (a locomotive/to instruct) and syntactic (noun/verb) properties, each affecting interpretation. Previous studies find homonym processing influenced by lexical frequency (Duffy et al. 1988) as well as syntactic and semantic context (Folk & Morris 2003; Swinney 1979; Tanenhaus et al. 1979). This cross-modal lexical-decision study investigates second language (L2) effects on homonym processing in the first language (L1). Participants were monolingual English speakers and Canadian English/French bilinguals who acquired L2 French at distinct periods. The early bilinguals revealed no significant differences compared to monolinguals (p = .219) supporting the Reordered Access Model (Duffy et al. 1988). However, the late bilinguals revealed longer reaction times, syntactic priming effects (p < .001), and lexical frequency effects (p < .001), suggesting a heightened sensitivity to surface cues influencing homonym processing in the L1 due to a newly-acquired L2 (Cook 2003).
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".