Perceptual narrowing during infancy: A comparison of language and faces
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this article, we begin with a summary of the evidence for perceptual narrowing for various aspects of language (e.g., vowel and consonant contrasts, tone languages, visual language, sign language) and of faces (e.g., own species, own race). We then consider possible reasons for the apparent differences in the timing of narrowing (e.g., apparently earlier for own race than for own species). Throughout we consider whether the evidence fits a model of maintenance/loss or is better characterized as enhancement/attunement to exposed categories. Finally, we consider evidence on the malleability of the timing and its implications for the role of endogenous factors versus learning in controlling when narrowing occurs. Overall, the comparison across domains revealed many similarities but also striking differences which lead to suggestions for future research.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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 it