Monolingual and bilingual children's social preferences for monolingual and bilingual speakers
Bibliographic record
Abstract
Past research has shown that young monolingual children exhibit language-based social biases: they prefer native language to foreign language speakers. The current research investigated how children's language preferences are influenced by their own bilingualism and by a speaker's bilingualism. Monolingual and bilingual 4- to 6-year-olds heard pairs of adults (a monolingual and a bilingual, or two monolinguals) and chose the person with whom they wanted to be friends. Whether they were from a largely monolingual or a largely bilingual community, monolingual children preferred monolingual to bilingual speakers, and native language to foreign language speakers. In contrast, bilingual children showed similar affiliation with monolingual and bilingual speakers, as well as for monolingual speakers using their dominant versus non-dominant language. Exploratory analyses showed that individual bilinguals displayed idiosyncratic patterns of preference. These results reveal that language-based preferences emerge from a complex interaction of factors, including preference for in-group members, avoidance of out-group members, and characteristics of the child as they relate to the status of the languages within the community. Moreover, these results have implications for bilingual children's social acceptance by their peers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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".