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Record W2907431287 · doi:10.5539/ijel.v9n1p261

American Orientalist Discourse: the Linguistic Formation and Transformation

2018· article· en· W2907431287 on OpenAlexvenueno aff
Mubarak Altwaiji

Bibliographic record

VenueInternational Journal of English Linguistics · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Studies and History
Canadian institutionsnot available
FundersNorthern Border University
KeywordsOrientalismIndependence (probability theory)Identity (music)Representation (politics)HistoryPoliticsSalientAmerican CenturySociologyPolitical scienceGender studiesAestheticsLawAncient historyPhilosophy

Abstract

fetched live from OpenAlex

The Middle East region had been the epicentre of American orientalist discourse since the American independence from Britain. After independence, American linguists, travellers, missionaries, politicians, sailors and traders scrutinized the anarchy and uncertainty of that region and employed them to produce works that prioritized American identity formation. This research rests on conducting an analysis of how American orientalism was created and how the various encounters between Arabs and America affected the linguistic course of this academia. This study considers the major encounters in the course of Arab-America relationship that brought major transformations to orientalism such as: the Barbary war, the creation of Israel, oil and terrorism. Since the American independence, American orientalism focused on building American identity in comparison with Arabs and their practices. Modern American orientalism has undergone various and huge transformations resulted mostly from formidable threats to American interests and the American retaliations to those threats. These encounters, whether political, economic or military, brought representation of Arabs to the top of American orientalist agenda and left a huge impact on image of Arabs in literature. Therefore, this study is based on the analysis of these different factors in order to know the different perspectives of this orientalism through its different stages.

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 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)0.028
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.960
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.014
GPT teacher head0.321
Teacher spread0.307 · 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 teacher head, not a consensus.

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

Citations5
Published2018
Admission routes1
Has abstractyes

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