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Record W3171440023 · doi:10.1017/s1366728921000225

In a bilingual state of mind: Investigating the continuous relationship between bilingual language experience and mentalizing

2021· article· en· W3171440023 on OpenAlexaff
Mehrgol Tiv, Elisabeth O’Regan, Debra Titone

Bibliographic record

VenueBilingualism Language and Cognition · 2021
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsMcGill University
Fundersnot available
KeywordsMentalizationPsychologyCognitive psychologyReading (process)InferenceTheory of mindNeuroscience of multilingualismCognitionDevelopmental psychologyLinguisticsComputer scienceArtificial intelligenceNeuroscience

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.307
Threshold uncertainty score0.519

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.035
GPT teacher head0.340
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2021
Admission routes1
Has abstractyes

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