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Record W7128538481 · doi:10.64903/1480-6800.20.2.183

Borrowed Words in Qatari Arabic: A Case Study of Knowledge of Meaning and Knowledge of Origin by Qataris

2017· article· W7128538481 on OpenAlexvenueno aff

Bibliographic record

VenueArab world geographer · 2017
Typearticle
Language
FieldArts and Humanities
TopicLinguistics, Language Diversity, and Identity
Canadian institutionsnot available
Fundersnot available
KeywordsMeaning (existential)ArabicFocus (optics)Sample (material)Semantics (computer science)

Abstract

fetched live from OpenAlex

Linguistic borrowing is a common, universal and intensively studied phenomenon. It is of interest to investigate this practice and its patterns in Qatari Arabic and to know to what extent the Qataris know the meaning and the origin of some borrowed words in Qatari Arabic. Thus, the researcher collected one hundred loanwords which are used in Qatari dialect and asked Qataris to identify the meaning and the origin of those words. The research sample comprised 240 Qataris equally divided according to gender. Then were separated into four age groups of females and four of males. The focus of this study is on the ability of the Qataris to identify the meaning and the origin of the borrowed words in question. In addition, the present paper investigates if there is any correlation between the dependent variables (gender, age and work/job) and knowledge of meaning and knowledge of origin.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0110.005
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.031
GPT teacher head0.287
Teacher spread0.256 · 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 designObservational
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

Citations0
Published2017
Admission routes1
Has abstractyes

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