Assertive and responsive conversational skills of Italian‐speaking late talkers
Bibliographic record
Abstract
BACKGROUND: Previous research on the pragmatic abilities of late talkers at 24 months of age indicates that they have difficulties initiating conversational interactions, but possess intact responsiveness skills. This study uses a parent-administered questionnaire for evaluating the conversational skills of late talkers and suggesting pragmatic intervention goals. AIM: To examine the conversational assertiveness and responsiveness of late talkers at 2 years of age. METHODS & PROCEDURES: A parent report measure, The Social Conversational Skills Rating Scale-Italian version, was administered to 30 parents of late talkers, 30 parents of typically developing children matched for age, and 30 parents of younger, typically developing children matched for vocabulary size. OUTCOMES & RESULTS: The late talkers received significantly lower ratings for both assertiveness and responsiveness in comparison with their age-matched peers. They did not differ significantly from the younger, vocabulary-matched group. Assertiveness and responsiveness mean ratings were positively correlated with vocabulary size for the age-matched group, but not for either of the other two groups. CONCLUSIONS: This study confirms a delay in the development of late talkers' social-conversational skills. An investigation of individual profiles suggests that some late talkers may require goals for vocabulary development as well as independent goals for developing pragmatic skills.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".