The a-map model: Articulatory reliability in child-specific phonology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article addresses a phenomenon of long-standing interest: the existence of child-specific phonological patterns that are not attested in adult language. We propose a new theoretical approach, termed the A(RTICULATORY)-MAP model, to account for the origin and elimination of child-specific phonological patterns. Due to the performance limitations imposed by structural and motor immaturity, children’s outputs differ from adult target forms in both systematic and sporadic ways. The computations of the child’s grammar are influenced by the distributional properties of motor-acoustic traces of previous productions, stored in episodic memory and indexed in the eponymous A-map. We propose that child phonological patterns are shaped by competition between two essential forces: the pressure to match adult productions of a given word (even if the attempt is likely to fail due to performance limitations), and the pressure to attempt a pronunciation that can be realized reliably (even if phonetically inaccurate). These forces are expressed in the grammar by two constraints that draw on the motor-acoustic detail stored in the A-map. These constraints are not child-specific, but remain present in the adult grammar, although their influence is greatly attenuated as a wide range of motor plans come to be realized with a similar degree of reliability. The A-map model thus not only offers an account of a problematic phenomenon in development, but also provides a mechanism to model motor-grammar interactions in adult speech, including in cases of acquired speech impairment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it