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Record W2946926297 · doi:10.5539/elt.v12n7p46

Implicit Demonstrative Reference With Reference to English Arabic Translation: The Case of Harry Potter and the Prisoner of Azkaban Novel

2019· article· en· W2946926297 on OpenAlexvenueno aff
Arwa N. T. Alhinnawi, Basem Shu. Al-Zughoul

Bibliographic record

VenueEnglish Language Teaching · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics, Language Diversity, and Identity
Canadian institutionsnot available
Fundersnot available
KeywordsDemonstrativeLiteral translationEquivalence (formal languages)LinguisticsScrutinyArabicDynamic and formal equivalencePsychologyNatural language processingComputer sciencePhilosophyMachine translation

Abstract

fetched live from OpenAlex

The present study aims at exploring the way in which English implicit demonstrative reference is rendered into Arabic through analyzing a number of sentences in the novel “Harry Potter and the Prisoner of Azkaban,” written by J. K. Rowling (2010), and its Arabic translated version by Ahmad Hassan Mohammed (2010). The scrutiny of the English implicit demonstrative reference shows that it can be translated into Arabic, whether implicitly or explicitly. This procedure is determined by the entailment of the demonstrative reference, whether it is clear and comprehensible, or unclear and incomprehensible. Also, the study has revealed that literal translation and formal equivalence present themselves as valid options in translating the English implicit demonstrative reference into Arabic. Recommendations of the study are stated at the end of the present research paper.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.008
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.020
GPT teacher head0.234
Teacher spread0.214 · 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 designQualitative
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
Published2019
Admission routes1
Has abstractyes

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