Arab-American Diaspora and the “Third Space”: A Study of Selected Poems by Sam Hamod
Bibliographic record
Abstract
Arab-Americans are an essential part of the multi-ethnic scene in the United States of America. They are increasingly making their voices louder. However, the process of Americanization has shaped Arab-American experience and literature both directly and indirectly. The early immigrants faced the pressures of assimilation into the American society, while also trying to preserve their Arab identity in the American-born generation. Cultural issues that are related to the immigrants’ experience, like biculturalism, bilingualism and dualism, are vitally depicted in Arab-American poetry. The American-born poets of Arab descent find in poetry a way through which they could express the dilemma of the Arab diaspora. Sam Hamod is one of the contemporary Lebanese-American literary figures whose works reflect the cultural conflicts from which the immigrants and their descendants suffer. Many of his poems deal with the concept of the “Third Space,” presented by the post-colonial theorist Homi K. Bhabha. It is a hybrid space in which the hyphenated individuals are stuck. In the multicultural and multiracial environment of the United States, the immigrants’ offspring occupy this in-between position where diverse cultures meet and clash in an endless process of identity splitting.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".