Migration politics: Mobilizing against economic insecurity in the United States and South Africa
Bibliographic record
Abstract
From the mid-2000s, the United States and South Africa, respectively, experienced significant pro-migrant and anti-migrant mobilizations. Economically insecure groups played leading roles. Why did these groups emphasize politics of migration, and to what extent did the very different mobilizations reflect parallel underlying mechanisms? Drawing on 41 months of ethnographic fieldwork and 119 interviews with activists and residents, I argue that the mobilizations deployed two common strategies: symbolic group formation rooted in demands for recognition, and targeting the state as a key source of livelihood. These twin strategies encouraged economically insecure groups to emphasize national identities and, in turn, migration. Yet, they manifested in different types of mobilization due to the varying characteristics of the groups involved, and the different national imaginaries and organizing legacies they had to draw upon. The analysis demonstrates the capacity of economically insecure groups to make collective claims. It also shows that within the context of anti-migrant nationalism, economic insecurity amplifies the significance of national belonging, citizenship, and migration as important terrains of collective struggle.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".