Bilingual and monolingual children prefer native-accented speakers
Bibliographic record
Abstract
Adults and young children prefer to affiliate with some individuals rather than others. Studies have shown that monolingual children show in-group biases for individuals who speak their native language without a foreign accent (Kinzler et al., 2007). Some studies have suggested that bilingual children are less influenced than monolinguals by language variety when attributing personality traits to different speakers (Anisfeld and Lambert, 1964), which could indicate that bilinguals have fewer in-group biases and perhaps greater social flexibility. However, no previous studies have compared monolingual and bilingual children's reactions to speakers with unfamiliar foreign accents. In the present study, we investigated the social preferences of 5-year-old English and French monolinguals and English-French bilinguals. Contrary to our predictions, both monolingual and bilingual preschoolers preferred to be friends with native-accented speakers over speakers who spoke their dominant language with an unfamiliar foreign accent. This result suggests that both monolingual and bilingual children have strong preferences for in-group members who use a familiar language variety, and that bilingualism does not lead to generalized social flexibility.
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 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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".