The Syntax of the Negation Marker Laa in Najdi Arabic: An HPSG Approach
Bibliographic record
Abstract
Negation is considered one of the controversial cross-linguistic areas of research. One of its interesting topics is the syntax of negation markers. This paper aims to contribute to the current linguistic research in negation through exploring one of the negation markers in Najdi Arabic: the negator laa. It first categories laa into three types according to its meaning and the syntactic constructions in which it occurs: the imperative laa, the conjunct particle laa, and the clausal laa. The syntactic properties of each one of these are described with sufficient examples illustrating them. Where appropriate, these properties are compared to those of the negator laa in Standard Arabic and other negators. In addition to the syntactic description of laa in its three types or uses, the paper presents a theoretical account for all the relevant syntactic properties of each type of the negator laa by using the framework of Head-driven Phrase Structure Grammar.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".