Beyond the foreign language effect: unravelling the impact of l2 proficiency on rationality
Bibliographic record
Abstract
Abstract This study investigated the impact of reading statements in a second language (L2) versus the first language (L1) on core knowledge confusion (CKC), superstition, and conspiracy beliefs. Previous research on the Foreign Language Effect (FLE) suggests that using an L2 elicits less intense emotional reactions, promotes rational decision-making, reduces risk aversion, causality bias and superstition alters the perception of dishonesty and crime, and increases tolerance of ambiguity. Our results do not support the expected FLE and found instead an effect of L2 proficiency: Participants with lower proficiency exhibited more CKC, were more superstitious and believed more in conspiracy theories, regardless of whether they were tested in L1 or L2. The study emphasises the importance of considering L2 proficiency when investigating the effect of language on decision-making and judgements: It—or related factors—may influence how material is judged, contributing to the FLE, or even creating an artificial effect.
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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 | 0.002 | 0.009 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".