MétaCan
Menu
Back to cohort
Record W2790907235 · doi:10.5539/ells.v8n1p83

Stress in English and Arabic: A Contrastive Study

2018· article· en· W2790907235 on OpenAlexvenueno aff
Mohammed Jasim Betti, Warkaa Awad Ulaiwi

Bibliographic record

VenueEnglish Language and Literature Studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic, Cultural, and Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLinguisticsStress (linguistics)ArabicPhenomenonContrast (vision)Similarity (geometry)Contrastive analysisComputer scienceEmphasis (telecommunications)Natural language processingArtificial intelligenceImage (mathematics)PhysicsPhilosophy

Abstract

fetched live from OpenAlex

This study is descriptive which describes and compares stress in English and Arabic in order to arrive at the points of similarity and difference. This is primarily achieved by showing its degrees, types, and functions, by surveying the literature available and by contrasting it in the two compared languages, conducting a contrastive study. The study hypothesizes that there is no difference between English and Arabic in terms of degrees, types and functions of stress. The study finds out that stress as a phenomenon exists in both languages and it is not phonemic. In addition, in both languages, it is connected with strong syllables, and its primary functions of stress are emphasis and contrast.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.309
Teacher spread0.298 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueEnglish Language and Literature StudiesSame topicLinguistic, Cultural, and Literary StudiesFrench-language works237,207