"The only thing one can do in America is emigrate”: South American Responses to the Venezuelan Migration Crisis
Bibliographic record
Abstract
Since 2015, approximately 4.8 million Venezuelans have fled from their homes in search of refuge from the country’s economic crisis and increasingly volatile political climate. As in other instances of mass displacement, they have not moved far, as nearly 80% of Venezuelan migrants have remained in continental South America. This essay analyzes how states and citizens have responded to the sudden influx of Venezuelan refugees from 2015 to the present. First, it shall offer a brief overview of the history of immigration policy in Latin America from the twentieth century to the early 2000s, exploring both regional and international initiatives. It then analyzes the novel, early responses of South American governments to Venezuelan refugees, finding, that, while regional and national policies were often devised with the intent of accommodation, in practice, these measures suffer from uneven implementation. Next, the paper interrogates the rightward shift in migration policy and discourse in recent years. While the extent and scope of policy change remain to be seen, the discursive and political turn towards restrictionism represents an alarming turn towards securitized immigration policy in the context of a conflict that shows no signs of stopping. Ultimately, this essay finds that the South American response to this crisis has been limited in its ability to provide accessible solutions, cooperate on a regional level, and maintain the same policies over time. Thus, it presents a challenge not only to individual states, but to the region’s ability to coordinate meaningful solutions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".