The Taboos of Occupation in Diana Abu Jaber’s Crescent and Naomi Shihab Nye’s Habibi
Bibliographic record
Abstract
The study explores the effect of occupation on the occupied population in both Diana Abu Jaber’s Crescent (2003) and Naomi Shihab Nye’s Habibi (1999). The impact of occupation is usually thought to be (and quite often are) taboos that cannot easily be revealed by the occupied, and if they are revealed, the audience will end up getting two different versions of the stories - one version from the occupier and the other version from the occupied. Abu Jaber and Nye express the taboos that are a result of the occupation of certain Middle Eastern countries, and more specifically, Iraq and Palestine. This paper attempts to show how both writers reflect which cannot be presented and spoken - the taboos of occupation - in their literary works, Crescent and Habibi. They even enhance these taboos by presenting them through different characters. There has been much literature written on both works, but there is still a lack in literature discussing how these authors have presented the taboos of occupation in Iraq and Palestine and how these writers took advantage of presenting these taboos through their narratives. Added to that, most of literature that has been written on current novels is about the political issues that these two countries have suffered from rather than the effect of these political issues on the people living in Iraq and Palestine. Second, most of the literature written has tackled each of the author’s works alone rather than written on the two novels together.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".