A Tropics of Estrangement: Ghurba in Four Scenes
Bibliographic record
Abstract
This essay traces the ambivalent work of ghurba (estrangement, exile, alienation) across four ethnographic scenes: Orthodox Christian activists in austerity Beirut refuse to abandon the corrupted world; a Syrian Islamic scholar in Jordan insists on the patient work of rehabilitation; Orthodox ascetics in a monastic community outside Tripoli turn to the hidden alienation borne in the world; and a Muslim calligrapher in Canada relinquishes the guarantee of ethical relation. Taken together, these scenes form a tableau of estrangement in the shared vocabulary of Eastern Christianity and Islam. Drawing on Ibn Khaldun's Muqaddimah–in its articulations of soul, community, and world always already shadowed by their undoing–we then situate these four scenes along spatio-temporal axes of destruction and production, city and desert, paradise and hellfire: a purgatorial topology which modulates what Agamben calls the contemporary destruction of experience.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.040 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| 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".