Speech articulation performance of francophone children in the early school years: Norming of the<b><i>Test de Dépistage Francophone de Phonologie</i></b>
Bibliographic record
Abstract
Good quality normative data are essential for clinical practice in speech-language pathology but are largely lacking for French-speaking children. We investigated speech production accuracy by French-speaking children attending kindergarten (maternelle) and first grade (première année). The study aimed to provide normative data for a new screening test - the Test de Dépistage Francophone de Phonologie. Sixty-one children named 30 pictures depicting words selected to be representative of the distribution of phonemes, syllable shapes and word lengths characteristic of Québec French. Percent consonants' correct was approximately 90% and did not change significantly with age although younger children produced significantly more syllable structure errors than older children. Given that the word set reflects the segmental and prosodic characteristics of spoken Québec French, and that ceiling effects were not observed, these results further indicate that phonological development is not complete by the age of seven years in French-speaking children.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".