Patterns and scales of expressive palatalization: Experimental evidence from Japanese
Bibliographic record
Abstract
This article argues for the existence of expressive palatalization (E-Pal) – a phonologically unmotivated process that applies in sound symbolism, diminutive constructions, and babytalk registers. It is proposed that E-Pal is grounded in iconic sound-meaning associations exploiting acoustic properties of palatalized consonants and thus is inherently different from regular phonological palatalization (P-Pal). A cross-linguistic survey of patterns of E-Pal in 37 languages shows that it exhibits a set of properties different from P-Pal. The case study focuses on patterns of palatalization in Japanese mimetic vocabulary and babytalk. Two experiments testing native speaker intuitions of these patterns revealed that both patterns exhibit place and manner asymmetries typical of cross-linguistic patterns of E-Pal. The cross-linguistic survey, the two experiments, and analysis of the origins and structural differences of E-Pal and P-Pal provide strong empirical and theoretical motivation to distinguish the two.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".