Variation in articulatory conflict resolution: Vowel allophony and consonant place adaptation in Chanka Quechua
Bibliographic record
Abstract
Abstract Cross-linguistically, vowel lowering/retraction are common strategies for resolving articulatory conflicts between high vowels and back consonants. Allophonic lowering of vowels /i/ and /u/ adjacent to uvulars has also been documented for several Southern Quechua dialects. For the Chanka dialect (Andahuaylas, Peru), traditional descriptions note similar allophony, but no studies have confirmed it. Unlike other Southern Quechua dialects, Chanka has only two dorsals, which contrast for both manner and place. Thus, Chanka may apply resolution processes differently, for reasons of production and/or perception. The current investigation considers to what extent articulatory conflict resolution between high vowels and the uvular consonant occurs in Chanka. Acoustic data from a controlled experiment include 3,827 Chanka vowels from 22 speakers, balanced for sex and location of residence. Despite an overall uvular effect found, intra- and interspeaker variation shows three different allophony patterns: categorical, null, and variable. A sex-based difference in patterns is also found for rural speakers, which hints at influence from Spanish on this process in Quechua given differing Spanish proficiencies. Results seem to indicate that consonant place adaptation may exist as an additional, innovative Chanka strategy, also with three variable patterns: stable uvular, stable velar, and homorganic with vowel. This flexibility in vowel and consonant place may partially relate to Chanka’s small phoneme inventory, which allows for a broader range of realizations without creating mergers. Speakers thus alternate between vowel lowering and consonant movement as solutions: sometimes the vowel place accommodates to the fricative like in many languages, and at other times the fricative follows the vowel.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".