Outward-sensitive phonologically-conditioned suppletive allomorphy vs. first-last tone harmony in Cilungu
Bibliographic record
Abstract
Abstract We present a case study of grammatical tone allomorphy in Cilungu (Bantu). Tense/Aspect/Mood designations (TAMs) are realized via co-exponence of prefixes, suffixes, and floating tones. In a minority of TAMs, there is allomorphy with the floating tones. For example, in the Recent Past one allomorph involves floating tone targeting the final mora of the stem ("Equation missing"<!-- image only, no MathML or LaTex -->) versus one targeting the stem’s second mora ("Equation missing"<!-- image only, no MathML or LaTex -->2). For all such allomorphic TAMs, the alternation is conditioned by the tone of subject agreement markers (SMs) at the left edge of the word. If the SM is high-toned the "Equation missing"<!-- image only, no MathML or LaTex -->variant occurs, but if it is toneless then "Equation missing"<!-- image only, no MathML or LaTex -->2occurs. We present two competing accounts of these data. Under a morphological account, we posit contextual realizational rules with multiple suppletive exponents conditioned by SM tone. In contrast, under a phonological account a ‘first-last tone harmony’ applies here, morphologically restricted to the context of SMs with a small set of TAMs. Such a harmony rule captures a generalization of these alternations: if the SM is high at the left edge then there is a grammatical high at the right edge, but if the left edge is toneless then grammatical tone does not fall on the right edge. We present several arguments in favor of the morphological analysis (suppletion) over a phonological one (harmony). Specifically, the patterns are not subject to phonological locality, other TAMs involving similar tone patterns are not subject to this harmony, and the proposed first-last tone harmony would be a highly phonologically-unnatural rule with little cross-linguistic support, and exceeding the computational properties of all well-known and established phonological operations. We conclude by discussing a major theoretical implication of the morphological account: this constitutes outward-sensitive phonologically-conditioned suppletive allomorphy, standardly argued to be unattested and/or impossible. Ultimately, we hold that under either account Cilungu presents a novel and important contribution to linguistic theory.
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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 | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".