Narrowing Perceptual Sensitivity to the Native Language in Infancy: Exogenous Influences on Developmental Timing
Bibliographic record
Abstract
The infancy literature situates the perceptual narrowing of speech sounds at around 10 months of age, but little is known about the mechanisms that influence individual differences in this developmental milestone. We hypothesized that such differences might in part be explained by characteristics of mother-child interaction. Infant sensitivity to syllables from their native tongue was compared longitudinally to sensitivity to non-native phonemes, at 6 months and again at 10 months. We replicated previous findings that at the group level, both 6- and 10- month-olds were able to discriminate contrasts in their native language, but only 6-month-olds succeeded in discriminating contrasts in the non-native language. However, when discrimination was assessed for separate groups on the basis of mother-child interaction-a 'high contingency group' and a 'moderate contingency' group-the vast majority of infants in both groups showed the expected developmental pattern by 10 months, but only infants in the 'high contingency' group showed early specialization for their native phonemes by failing to discriminate non-native contrasts at 6-months. The findings suggest that the quality of mother-child interaction is one of the exogenous factors influencing the timing of infant specialization for speech processing.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".