On the Syntax of Sentential Negation in Yemeni Arabic
Why this work is in the frame
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Bibliographic record
Abstract
In this paper we explore the system of negation in modern Arabic dialects with a particular focus on Yemeni Arabic (Raymi dialect). The data observed in this dialect incorporate important and novel facts related to the syntax of sentential negation in Arabic. This includes the distribution of negation patterns and the interaction between negation and negative polarity items, which challenges the two widely adopted analyses for sentential negation in Arabic: The Spec-NegP analysis and the discontinuous Neg analysis. In this paper we argue that neither analysis can provide an adequate account of Raymi Arabic facts. Instead, a more recent analysis, the Spilt-Neg analysis, can accommodate them. In addition, in the study we provide empirical evidence in support of the Higher-Neg analysis, wherein Neg is projected higher than T in the derivation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.111 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it