Boosting the input: 9‐month‐olds’ sensitivity to low‐frequency phonotactic patterns in novel wordforms
Bibliographic record
Abstract
To learn their first words, infants must attend to a variety of cues that signal word boundaries. One such cue infants might use is the language-specific phonotactics to track legal combinations and positions of segments within a word. Studies have demonstrated that, when tested across statistically high and low phonotactics, infants repeatedly reject the low-frequency wordforms. We explore whether the capacity to access low-frequency phonotactic combinations is available at 9 months when pre-exposed to wordforms containing statistically low combinations of segments. Using a modified head-turn procedure, one group of infants was presented with nonwords with low-frequency complex onsets (dr-), and another group was presented with zero-frequency onset nonwords (dl-). Following pre-exposure and familiarization, infants were then tested on their ability to segment nonwords that contained either the low- or the zero-frequency onsets. Only infants in the low-frequency condition were successful at the task, suggesting some experience with these onsets supports segmentation.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".