Comparison of measures of morphosyntactic complexity in French-speaking school-aged children
Bibliographic record
Abstract
This study examined the validity and reliability of different measures of morphosyntactic complexity, including the Morphosyntactic Complexity Scale (MSCS), a novel adaptation of the Developmental Sentence Scoring, in French-speaking school-aged children. Seventy-three Quebec children from kindergarten to Grade 3 completed a definition task and a narration task. Mean length of utterance (MLU), clause density and MSCS global score, average frequency scores and average complexity scores were calculated from the transcripts of the two contexts. MLU, clause density and MSCS global score were correlated with vocabulary knowledge and narrative skills, and they increased as a function of school level, suggesting that they are valid measures of morphosyntactic complexity. Moreover, the three scores were correlated across contexts, suggesting that they are also reliable measures. However, no MSCS average frequency or average complexity score was found to be both valid and reliable. These findings will guide researchers and practitioners who desire to assess the language skills of French-speaking school-aged 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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".