Reflexes of exponent movement in inflectional morphology
Bibliographic record
Abstract
Abstract Seemingly non-local phonological operations triggered by inflectional exponents have been observed in a number of languages. Focussing on de-spirantization in Barwar Aramaic, accent shift in Lithuanian,ni-insertion in Quechua,rukirule application in Sanskrit, and vowel harmony in Kazakh, we argue that these phenomena should be analyzed as strictly local phonological reflexes of movement in a pre-syntactic autonomous morphological component. Such morphological movement is shown to arise without further assumptions under the approach to inflectional morphology based on Harmonic Serialism (McCarthy 2016) developed in Müller 2020. Here, each morphological operation immediately gives rise to an optimization procedure, morphological structure-building is subject to simple alignment constraints, and counter-cyclic operations are precluded. Against this background, phonological reflexes of movement are predicted to show up when a potentially complete word triggers a phonological cycle, which is then followed by morphological movement. Finally, we argue that constraint-driven morphological movement is superior to alternative accounts based on (i) non-local phonology, (ii) base-derivative faithfulness, (iii) phonological movement, (iv) counter-cyclic operations (interfixation, lowering, local dislocation), (v) syntactic movement, and (vi) strata.
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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 | 0.002 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".