Exploring how preschoolers who stutter use spoken language during free play: A feasibility study
Bibliographic record
Abstract
Purpose: Play is critically important for the healthy development of children. This study explored the viability of a methodology to investigate how preschoolers who stutter use language in play with peers.Method: Transcripts of peer-directed utterances of four preschoolers who stutter and four matched non-stuttering children during free play were analysed for measures of verbal output (numbers of utterances and words), length and complexity of utterances (mean length of communication unit and syntactic complexity), and lexical diversity (number of different words, type token ratio and vocd).Result: Viable speech samples were obtained. Verbal output scores of two children who stutter were the same or higher than their matched controls whereas mean length of communication unit and syntactic complexity scores for three children who stutter were lower than their matched controls. In 22 of the 24 comparisons across number of different words, type token ratio, and vocd, scores of children who stutter were the same or higher than their matched controls.Conclusion: Interpretation of data is limited by the small sample size and lack of standardised testing. However, results indicate that the methodology has promise for future research into the way preschoolers who stutter use spoken language during play and the quality of their play.
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 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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".