Bilingual social cognition: Investigating the relationship between bilingual language experience and mentalizing
Bibliographic record
Abstract
Mentalizing is a dynamic form of social cognition that is strengthened by language experience and proficiency. Similarly, bilingual children and adults consistently outperform monolinguals on traditional tasks. Here, we probe the relationship between bilingual language experience and mentalizing by investigating first (L1) versus second language (L2) mentalizing, and whether individual differences in language diversity continuously pattern with mentalizing judgments. We tested sixty-one bilingual adults on an on-line reading and inference task that compared mental state and logical inferences. We find that all readers judge mental state inferences as less coherent than logical inferences, but L2 readers make this judgment for mental state inferences faster than L1 readers. Moreover, L2 readers overmentalize logical inferences compared to L1 readers. In addition, greater language diversity patterns with higher mentalizing for mental state inferences across all readers. Together, we find evidence in favor of a positive relationship between bilingual language experience and mentalizing.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".