Transnational Perspectives: War, Power, and Violence in the Work of Etel Adnan
Bibliographic record
Abstract
This paper seeks to investigate how national literature transcends local borders and interconnects with images and realities of war, power, and violence in a transnational context. The current study attempts to position the contemporary Arab-American writer and poet, Etel Adnan (1925), within a transitional milieu that engages questions regarding what type of associations may be made among the themes under study and how dialogue between nationalism and literature does meet from the lens of a transnational perspective. Drawing upon a wide range of transnational theories and criticism, borderland theory, and Anglophone Arab feminist writing, I attempt to examine how Adnan questions, mediates, and reflects upon her transnational experience in light of what scholars such as Pries (2001), Ramazani (2009), Parker and Young (2013), Smith and Guarnizo (1998), and Jakubowicz (2012) have negotiated in this field. Through a selection of Adnan’s genres and literary styles, the paper focuses on how issues of transnational ethnicity, culture, race, history, politics and multiple belongings intersect in the transnational landscapes that signify the vitality of contemporary Arab-American women’s writing and give voice to the peculiarities of female subjectivity beyond borderlands. In this sense, the paper will bring to light the emerging transnational literary discourse and variations of its expressions and forms that resist the confines of national spaces and state borders.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.013 |
| 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".