Bibliographic record
Abstract
Abstract This paper addresses typological differences in subject–verb agreement and provides evidence that transitive subject agreement need not always involve a high functional head, namely T0, but may instead be the result of a local relation between the subject and a low functional head, v0. In Mayan languages, grammatical relations are head‐marked on the predicate through two series of morphemes, known as “Set A” (ergative/possessive) and “Set B” (absolutive). I argue that Set A morphemes reflect a local relationship of agreement between v0and the transitive subject in its low base position and, in an analogous structural configuration in the nominal domain, between a possessive n0head and the possessor. Crucially, I show that no higher functional projection is involved. This is important in light of proposals that ergative agreement systems are epiphenomenal, resulting from standard nominative agreement from T0which is blocked from agreeing with morphologically case‐marked ergative subjects (Woolford ). In this paper, I examine the morphologically ergative Mayan language Ch'ol to show that true ergative agreement is possible even in the absence of morphological case. This paper has implications for the typology of ergative case and agreement systems and contributes to our understanding of the nature of agreement and clitic doubling.
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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 | 0.001 | 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 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".