Second language experience impacts first language irony comprehension among bilingual adults
Bibliographic record
Abstract
Recently, core components of irony processing (e.g., mental-state reasoning, executive control, and metalinguistic awareness) have been tentatively linked to bilingual experience. Thus, we investigated whether bilingual experience modulates irony comprehension during first language reading, and also how bilingual adults comprehend irony in positive vs. negative contexts (i.e., ironic compliments vs. criticisms, respectively). We deliver three main findings. First, bilinguals are faster at processing ironic criticisms than ironic compliments, and they find ironic criticisms more sensible than ironic compliments in their L1, much like past findings among monolinguals. Second, individual differences in bilingual experience modulate comprehension of ironic statements. Specifically, readers with high global L2 proficiency find ironic statements more sensible than readers with low global L2 proficiency, regardless of the valence of the preceding context. Third, individual differences in global L2 proficiency further predict the speed of L1 irony comprehension: following a positive scenario, greater global L2 proficiency patterns with faster processing of irony compared to literal statements. Together, these data suggest that second language experience may be linked to irony processing in the first language. While the precise mechanism underlying this relationship remains open, potential sources may be rooted in flexible social cognition or executive functions.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".