American Orientalist Discourse: the Linguistic Formation and Transformation
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.018 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".