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Record W3006887957 · doi:10.5539/ijel.v10n2p331

On the Syntax of Sentential Negation in Yemeni Arabic

2020· article· en· W3006887957 on OpenAlex
Abdulrahman Alqurashi, Mukarram Abduljalil

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of English Linguistics · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsnot available
Fundersnot available
KeywordsNegationSyntaxLinguisticsArabicFocus (optics)Computer scienceNatural language processingPolarity (international relations)AgreementPhilosophyPhysics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.111
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.534
Threshold uncertainty score0.897

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.111
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.250
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it