A motor differentiation model for liquid substitutions in children’s speech
Bibliographic record
Abstract
Studies of lip-jaw coordination in children have shown a lack of motor differentiation between anatomically coupled articulators in young childrens speech [Green & al. 2000, JSLHR 43: 239–255]. A model is described in which children contending with their developing motor systems generally strive to reduce the degrees of freedom of complex anatomical structures (e.g., the tongue). The claim is pursued that segmental substitutions (e.g., /w/ replacing /r/ or /l/) are the result of specific compensation strategies which aim to simplify the complexity of the articulatory task. The proposal that gestural simplification may dictate substitution strategies for liquid consonants has been suggested previously [Studdert-Kennedy & Goldstein 2003, Language Evolution, Oxford U. Pr. 235-254]. It is proposed here that gestural simplification may be achieved via one of two basic mechanisms: gestural omission and stiffening (and hence merger), and that these two mechanisms account for all of the commonly attested substitutions for English /r/ and /l/. Supporting data are presented from ultrasound studies of: postvocalic /r/ production of an 11-month-old female speaker of English, liquid production of a group of 3–5-year-old speakers of English, and liquid production and substitutions in the speech of adolescent speakers of English with speech and hearing disorders.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".