Ghosts, Guests, Hosts: Rethinking “Illegal” Migration and Hospitality Through Arab Diasporic Literature
Bibliographic record
Abstract
This article examines and compares narratives of migration developed by contemporary Arab diasporic writers living in North America (both in the United States and Quebec) and in Europe (France and Italy). These writers, I argue, chronicle the painful and often banished from view experience of contemporary “illegal” migrants, anchoring the singular fictional or autobiographical story to the “real” world of migration and to the larger sociopolitical and historical context. Through an original style that blends fresh creativity and deep humanity, the writers addressed in this article complicate mainstream representations of migrants as threatening Others or unwelcomed guests; they further resituate hospitality at the center of current discussions about migration, surprising the reader with creative reformulations of Derrida's conceptualization of hospitality that are both entertaining and politically engaged.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.040 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| 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".