ManyBabies 5: A large-scale investigation of the proposed shift from familiarity preference to novelty preference in infant looking time
Bibliographic record
Abstract
Much of our basic understanding of cognitive and social processes in infancy relies on measures of looking time, and specifically on infants’ visual preference for a novel or familiar stimulus. However, despite being the foundation of many behavioral tasks in infant research, the determinants of infants’ visual preferences are poorly understood, and differences in the expression of preferences can be difficult to interpret. In this large-scale study, we test predictions from the Hunter and Ames model of infants' visual preferences. We investigate the effects of three factors predicted by this model to determine infants’ preference for novel versus familiar stimuli: age, stimulus familiarity, and stimulus complexity. Drawing from a large and diverse sample of infant participants (minimum expected sample size N = 1,280), this study aims to provide empirical evidence for a robust and generalizable model of infant visual preferences, leading to a more solid theoretical foundation for understanding the mechanisms that underlie infants’ responses in common behavioral paradigms. Moreover, we hope that our findings will guide future studies that rely on infants' visual preferences to measure cognitive and social processes.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".