A Comparison of Single Words and Conversational Speech in Phonological Evaluation
Bibliographic record
Abstract
PURPOSE: The purpose of the current study was to compare conversational speech samples with single-word samples that were partially tailored to the participants' individual phonological profiles, using aspects of nonlinear phonological frameworks as a basis for evaluation. METHOD: There were 20 participants in the study, ranging in age from 3;0 to 10;5 (years;months). The Computerized Articulation and Phonology Evaluation System (J. J. Masterson & B. Bernhardt, 2001) was used to elicit single-word productions. RESULTS: Both group and individual comparisons indicated very few differences in accuracy or treatment ramifications. The time required to elicit and transcribe the conversational samples was typically 3 times greater than the time required for the single-word task. The single-word task elicited more of the English-language targets. CONCLUSIONS: The results of this study suggest that a single-word task tailored to some extent to the client's phonological system gives sufficient and representative information for phonological evaluation. A brief conversational sample remains useful for examining prosody, intelligibility, and other aspects of language, and as a check on the representativeness of the single-word sample.
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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 | 0.005 | 0.026 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".