Crossing the Border: Arab-American Literature and the Politics of Exclusion
Bibliographic record
Abstract
Abstract This paper attempts to trace the development of Arab-American literary tradition through three distinct generations—each of which responds quite differently to the identity politics, cultural hybridity, subversion of orientalist gaze, and the crisis of belonging amidst the inevitable multifacetedness of the Arab-American community. The literary works of the contemporary Arab-American writers are engaged with the idea of the American landscape as a long-term rather than a provisional home. In other words, this new generation of writers manages to hover over the divide between the two cultures and view the Arab world from the American soil. The paper finally approaches the Post-9/11 Arab-American novel in terms of receptiveness, characteristics, challenges, and future outlook. I argue that for the contemporary Arab-American novel to flourish, the integration of Arab experience into the American fabric, in the sense that themes and subject matters related to both sides of the hyphen, should be acknowledged as a cultural necessity. Ironically, this is the best way for Arab-American novelists to bring their distinct voices to the multi-vocal mainstream culture, to carve a niche for themselves. The useful analogy is the literary cultural expressions and experiences of the Asian, African or Canadian communities on the American soil; they are distinct, but not different from the cultural traditions of other diaspora communities. Keywords: Arab-American, Cultural Hybridity, Identity Politics, Post-/911 Novel, Neo-Orientalism.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.044 | 0.047 |
| Scholarly communication | 0.020 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".