Palatalization and glide strengthening as competing repair strategies: Evidence from Kirundi
Bibliographic record
Abstract
Alternations involving place-changing palatalization (e.g. t+j → ʧ in spirit – spiritual) are very common and have been a focus of much generative phonological work since Chomsky & Halle’s (1968) ‘Sound Pattern of English’. The interest in palatalization and its mechanisms (see e.g. Sagey 1990; Chen 1996; Bateman 2007) has somewhat obscured the question of how these processes fit into a wider typology of segmental alternations. What happens when palatalization fails to apply? Do other processes take its place and apply under the same circumstances? In this paper, I argue for a close functional and formal affinity between place-changing palatalization and one such process, palatal glide strengthening (e.g. p+j → pc). As evidence I present data from Kirundi (Bantu) on the realization of consonant + palatal and velar glide sequences within and across morphemes. As will be shown, palatalization and glide strengthening in Kirundi work in parallel, affecting different subsets of consonants. Specifically, palatalization targets C+j sequences with laryngeals, velars, nasal coronals, and – across morpheme boundaries – non-nasal coronals. In contrast, glide strengthening targets C+j sequences with labials and – within morphemes – non-nasal coronals. In addition, glide strengthening applies to within- and across-morpheme consonant + velar glide sequences, producing a set of outputs (e.g. m+w → mŋ) similar to C+j sequences. I further present a unified Optimality Theoretic (Prince & Smolensky 1993/2004) account of these seemingly disparate phenomena as both arising from different rankings of constraints prohibiting consonant + glide sequences (parameterized by place and/or manner) and various feature-specific agreement and faithfulness constraints. Finally, I explore typological predictions of this account, reviewing several remarkably similar cases of C + glide resolution patterns from other languages, and outlining questions for further research on consonant-vowel/glide interactions.This article is part of the special collection: Palatalization
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".