Bibliographic record
Abstract
Abstract Arabic exceptive constructions involve an intricate interaction among word order, negation, and case assignment resulting from syntactic restrictions imposed on the argumental, appositional, and adjunctive functions of exceptive phrases. The morphosyntactic complexities in Arabic exceptives cast doubt on the adequacy of previous analyses that exceptive particles are prepositions, focal adverbs, or coordinating conjunctions, and they also lead the paper to argue for more principled accounts in which exceptive particles are analysed as functional heads that project into an ExP ‘exceptive phrase’ which exists in two distinct configurations. The first includes an exceptive marker carrying [Acc- Case] ‘accusative case’ and [DS] ‘domain subtraction’ features when the ExP is an adjunct introduced by late Merge. The second includes a negative determiner which selects and c-commands the exceptive particle and deactivates/ suspends its [Acc-Case], consequently, the case feature of the ExP-complement is valued by percolation from D which combines with the exceptive marker to form a discontinuous focus particle with a [DR] ‘domain restriction’ feature.
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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 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".