Bridging people and perspectives: General and language-specific social network structure predict mentalizing across diverse sociolinguistic contexts.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Mentalizing, or reasoning about others' mental states, is a dynamic social cognitive process that aids in communication and navigating complex social interactions. We examined whether exposure to diverse perspectives, afforded by occupying influential social network positions, predicted bilingual adults' performances on a behavioral mentalizing rating task in regions of high and low linguistic diversity. We calculated the degree to which respondents' social network position generally bridged unconnected others (i.e., general betweenness) and specifically bridged language communities (i.e., language betweenness). General betweenness predicted mentalizing performance regardless of region, whereas language betweenness only predicted mentalizing in a high linguistic diversity region, where bilingualism is ubiquitous and mentalizing to resolve perspective differences on the basis of language may be an adaptive cognitive strategy. These results indicate that human cognition is sensitive to social context and adaptive to the sociolinguistic demands of the broader environment. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it