Xenophobia, International Migration and Human Development
Bibliographic record
Abstract
In the continuing discussion on migration and development, the vulnerability of all migrant groups to exploitation and mistreatment in host countries has been highlighted along with an emphasis on protecting their rights. However, xenophobia has not yet received explicit attention although anti-migrant sentiments and practices are clearly on the rise even in receiving countries in developing regions. Despite gaps in existing empirical work, research and anecdotal evidence exposes pervasive forms of discrimination, hostility, and violence experienced by migrant communities, with the latter becoming easy scapegoats for various social problems in host countries. This study attempts to insert xenophobia in this debate on migration and development by examining the growth of this phenomenon in host countries in the South. It provides short accounts of xenophobia witnessed in recent times in five countries including South Africa, India, Malaysia, Libya, and Thailand. The ambiguity surrounding the concept is discussed and crucial features that define xenophobia are outlined. A variety of methods to study it are likewise identified. Using a wide range of examples from diverse contexts, the paper explores possible reasons for the intensification of xenophobia. The final sections of the paper briefly outline the developmental consequences of rampant xenophobia for migrant and host populations while examining policy options to tackle it.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".