Quantifying sources of variability in infancy research using the infant-directed speech preference
Bibliographic record
Abstract
The field of psychology has become increasingly concerned with issues related to methodology and replicability. Infancy researchers face specific challenges related to replicability: high-powered studies are difficult to conduct, testing conditions vary across labs, and different labs have access to different infant populations, amongst other factors. Addressing these concerns, we report on a large-scale, multi-site study aimed at 1) assessing the overall replicability of a single theoretically-important phenomenon and 2) examining methodological, situational, cultural, and developmental moderators. We focus on infants’ preference for infant-directed speech (IDS) over adult-directed speech (ADS). Stimuli of mothers speaking to their infants and to an adult were created using semi-naturalistic laboratory-based audio recordings in North American English. Infants’ relative preference for IDS and ADS was assessed across 67 laboratories in North America, Europe, Australia, and Asia using the three commonly-used infant discrimination methods (head-turn preference, central fixation, and eye tracking). The overall meta-analytic effect size (Cohen’s *d*) was 0.35 [0.29 - 0.42], which was reliably above zero but smaller than the meta-analytic mean computed from previous literature (0.67). The IDS preference was significantly stronger in older children, in those children for whom the stimuli matched their native language and dialect, and in data from labs using the head-turn preference procedure. Together these findings replicate the infant-directed speech preference but suggest that its magnitude is modulated by development, native language experience, and testing procedure.
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How this classification was reachedexpand
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 | 0.008 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".