In a bilingual state of mind: Investigating the continuous relationship between bilingual language experience and mentalizing
Bibliographic record
Abstract
Abstract Mentalizing, a dynamic form of social cognition, is strengthened by language experience. Past research has found that bilingual children and adults outperform monolinguals on mentalizing tasks. However, bilingual experiences are multidimensional and diverse, and it is unclear how continuous individual differences in bilingual language experience relate to mentalizing. Here, we examine whether individual differences in bilingual language diversity, measured through language entropy, continuously pattern with mentalizing judgments among bilingual adults, and whether this relationship is constrained by first vs. second language reading. We tested sixty-one bilingual adults on a reading and inference task that compared mental state and logical inferences. We found that greater language diversity patterned with higher mentalizing judgments of mental state inferences across all readers, and that L2 readers attributed more mentalizing to logical inferences compared to L1 readers. Together, we found evidence of a positive relationship between continuous individual differences in bilingual language diversity 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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".