Differential marking of direct objects in Monastirli <i>džudezmu</i>: a case study in Judeo-Spanish morphosyntax
Bibliographic record
Abstract
Abstract This article presents a case study on the differential marking of direct objects (DOM) in Balkan Judeo-Spanish, an endangered language (sub)group that still lacks detailed, systematic documentation of its (comparative) morphosyntax. Countering recent claims that the phenomenon is frequently absent in Judeo-Spanish, I demonstrate the robust presence of so-called a-marking as a highly systematic, multi-dimensional DOM strategy in early 20th century fieldwork recordings from the understudied dialect of Monastir (present-day Bitola, North Macedonia). I show that, in our corpus, a-marking in transitive (S)V(S)O(S) structures is primarily regulated by (grammatical) animacy/person and (syntactic) definiteness, such that indefinite DOs are excluded and specificity plays no role. Theoretically, the empirical distribution of a-marking broadly conforms with, yet – crucially – cannot be fully subsumed under, scale-based hierarchies that model DOM in terms of referential prominence. Rather, our findings support the conclusion that a-marking of the DO occurs if and only if the argument is syntactically specified for animacy/person and definiteness. From the typological perspective, the (non-)coincidence of Monastirli a-marking with a co-referential accusative clitic exhibits a hitherto undescribed distribution distinct from other patterns documented for (Balkan) Romance. The present article thus not only advances description of, and inquiry into, the cross-linguistic landscape of DOM, but contributes more broadly to redressing the conspicuous absence of empirical and theoretical investigation into Judeo-Spanish dialect syntax.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".