Language-Specific Sound-Shape Matching at 12-Months of Age
Bibliographic record
Abstract
By 12 months of age, infants exhibit behavioral sensitivity to sound symbolism (e.g. sound-shape correspondences) when they hear universally sound symbolic pseudowords (e.g. “bouba,” “kiki”). Here, we investigated whether infant’s sensitivity to sound-shape correspondences is affected when they hear language-specific sound symbolic words. Using the spontaneous preference-looking paradigm, we tested 12-month-old monolingual Spanish (n = 13) and Basque (n = 16) infants matching Spanish-like pseudowords (i.e. “bubano,” “raceto”) with rounded and spiky shapes. These pseudowords were created by Spanish-Basque bilingual adults, who then rated pseudowords as more Spanish or Basque-like, and more rounded or spikey-like. Infants were presented with eight congruent (e.g. “bubano” presented with a rounded shape) and incongruent (e.g. “bubano” presented with a spiky shape) trials. Both Spanish and Basque-learning infants displayed similar increased sensitivity to incongruent than to congruent trials. We found weak evidence that language background modulates sound-shape correspondence. These results suggest that at 12 months of age, specific language experience (e.g. Spanish vs. Basque) most likely does not alter sound-shape bias when hearing Spanish-like sound combinations. This study was the first to utilize language-specific instead of language nonspecific stimuli. Nonetheless, similar to previous investigations, the sound-shape bias effect was exhibited at 12 months of age in both language groups.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".