Migration as a Method of Coping with Turbulence Among Palestinians
Bibliographic record
Abstract
Migration is one way individuals and families cope with economic uncertainty and political turbulence. Palestinians have used migration as a means to find economic stability and opportunities for their children since 1948, due to continuous strife in and displacement from their homeland. Built on earlier studies, this article discusses the findings of in-depth-interviews and focus groups with low-income Palestinians from Amman, Jordan now living in Chicago concerning their quality of life and the indicators they use to assess it. The authors found that these Palestinians see life in the United States as much richer in economic and educational opportunities than Jordan, but Jordan is viewed as being safer and providing stronger social supports. Consequently, they see their migration as circular, with movement plans timed to maximizing the best features of each country. Rather than seeking to settle permanently in the United States, they speak about living transnationally — moving between the two countries at different stages in their own and their children’s life cycles. Since September llth, 2001 however, the social and policy context in the United States has changed, especially for Arabs and Muslims. After describing some of these changes, the authors speculate that they may limit and change the character of Palestinian migration from Jordan, making a transnational lifestyle more risky and life in the US less tolerable. They find preliminary support for this idea in a survey of 33 residents of Amman and in an examination of data from the US visa lottery.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".