“PEOPLE EAT PEOPLE”: THE INFLUENCE OF SOCIOECONOMIC CONDITIONS ON EXPERIENCES OF DISPLACEMENT IN JORDAN
Bibliographic record
Abstract
Abstract This article explores the ways in which refugee and host experiences of displacement in Jordan between 2010 and 2013 were articulated in a socioeconomic register that coincided with, but was also independent of, both state biopower and historical cross-border regionalisms. I argue that this register became salient due to a shared understanding of everyday life as characterized by what I termhunger, a state of depredation where “people eat people” to attain their own well-being. In pursuing this argument, the article has two goals: to show how Iraqis and Jordanians negotiated the complexities of living together in hunger by censuring individuals—locals and foreigners, rich and poor—who contributed to producing hunger rather than to alleviating it, and by consciously resisting the corrosive effects of hunger on social relations; and, more generally, to challenge universalizing understandings of refugee experiences according to which local tensions between refugees and hosts are derivative of a globalized antiforeigner discourse.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| 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".