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Record W2970545957 · doi:10.5539/ijel.v9n5p227

The Norms of Address Terms in Arabic: The Case of Saudi Speech Community

2019· article· en· W2970545957 on OpenAlex

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 · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsnot available
FundersMajmaah University
KeywordsFormalityArabicTerm (time)GirlPsychologyLinguisticsSocial psychologySociologyDevelopmental psychology

Abstract

fetched live from OpenAlex

This paper investigates the address norms used in the Saudi Arabic speech community. The study examines address term usage in five different contexts: family, neighbors, workplace, school and strangers. The study seeks answers for two questions: (1) What address forms do Saudi Arabic speakers use to address each other? (2) What factors cause a difference in use of one term over another? Responses were collected from 40 Saudi speakers of Arabic who were divided evenly based on age and gender. The findings reveal nine key categories as fundamental techniques used by Saudi Arabic speakers to address one another including first names, teknonyms, common names, kin terms, kin term along with first name, terms of endearment, titles, occupation and address by gender (boy/girl). Social factors like age, gender, socio-economic status, level of formality as well as degree of intimacy and occupation were also essential in determining form usage.

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)0.001
metaresearch head score (Gemma)0.011
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 score0.818
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.011
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 science0.0010.000
Research integrity0.0000.001
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 head0.036
GPT teacher head0.315
Teacher spread0.279 · 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