The Role of Semantic Transparency in the Processing of Verb-particle Constructions by French-English Bilinguals
Bibliographic record
Abstract
Verb-particle constructions (phrasal verbs) are a notoriously difficult aspect of English to acquire for second-language (L2) learners.This study was conducted to assess whether L2 English speakers would show sensitivity to the subtle semantic properties of these constructions, namely the gradations in semantic transparency of different verb-particle constructions (e.g., finish up vs. chew out).L1 French, L2 English bilingual participants completed an off-line (explicit) survey of similarity ratings, as well as an on-line (implicit) masked priming task.Bilinguals showed less agreement in their off-line ratings of semantic similarity, but their ratings were generally similar to those of monolinguals.On the masked priming task, the more proficient bilinguals showed a pattern of effects parallel to monolinguals, indicating similar sensitivity to semantic similarity at an implicit level.These findings suggest that the properties of verb-particle constructions can be both implicitly and explicitly grasped by L2 speakers whose L1 lacks phrasal verbs.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".