An Investigation of Structures and Prosodic Features of Child Directed Speech During Shared Reading
Bibliographic record
Abstract
Child-directed speech objectives are a) attract and hold baby’s attention, b) help process of breaking down language into understandable chunks , c)make the conversation more predictable by keeping the conversation. This paper compares the structures and prosodic feature used during shared reading by two Iranian mothers of two different aged children, i.e. 2.5 and 4. This study carried out through mothers’ speech recording while describing picture book to r children. The compared data from transcription of sessions revealed that the amount of one-word or tow-word utterances and imperative and declarative ones along with prosodic feature (intonation) ,used by mothers ,depends on child semantic knowledge and age. Here declarative utterances were used the most and imperatives the least. The reasons to use different intonation referred to their age to draw their attention.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".