Children with atypical phonological development : assessment profiles and rates of change
Bibliographic record
Abstract
Children with protracted phonological development (PPD) require an assessment that reflects factors associated with their speech delay, in order to formulate maximally effective intervention goals. This study examined issues relating to the assessment and classification of children with PPD, as having a perceptual or motoric basis, and factors or patterns of performance that might be predictive of severity or change in PPD. Thirteen English-speaking preschool children (4;0 to 5;6) with moderate to severe PPD participated in this study. All children had normal oral structures, hearing and vocabulary comprehension. Data were collected in an initial assessment and again 3-5 months later. Tasks at assessment included the Computerized Articulation and Phonology Evaluation System (CAPES, Masterson & Bernhardt, 2001), the Speech Assessment and Interactive Learning System (SAILS, AVAAZ, 1994) perceptual test, the Prereading Inventory of Phonological Awareness (PIPA , Dodd, Crosbie, Mcintosh, Teitzel & Ozanne, 2003), maximum performance tasks (MPTs) using monosyllabic and trisyllabic sequences, and the gross and fine motor subscales from the Child Development Inventory (CDI, Ireton,1992) parent questionnaire. The follow-up assessment consisted of CAPES, a subset of SAILS, a selection of MPTs, and a parent version of the Speech Participation and Activity of Children (SPAA-C, McLeod, 2004) questionnaire. At follow-up, all children showed improvement in phonology. Analysis of the initial assessment tasks did not clearly reveal motoric or perceptual bases for the PPD or factors that were predictive of gain in phonology 3-5 months later. Descriptive comparisons of children's performance patterns on the initial assessment tasks suggested that phonemic perception might be correlated to severity and/or change in phonology.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".