Bibliographic record
Abstract
With my belief that there is not a comprehensive theory of adverb position, Iatridou (1990), Bobaljik & Jonas (1996), in this paper, I investigate the morph-syntax and distribution of adverbs in one of the Saudi dialects, Saudi Northern Region Dialect of Arabic (SNRDA); a dialect that is spoken in the Northern Region of Saudi Arabia. I will show that adverbs at least in SNRDA are not descriptively as simple as it is assumed for other dialects of Arabic studied by Nuha (2005) and in the Modern Standard Arabic (MSA) investigated by Fassi (1997, 1998). What is interesting in this dialect is that intonation plays role in where the adverbs appear and how they are interpreted; in addition, with the change of the adverb position, there is a change in the meaning. The contribution of this paper is that it discusses adverbs in a dialect which many of its syntactic facts remain largely un-described and adds to our understanding of the syntactic behavior of the adverbs.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".