"Your Tired, Your Poor, Your Huddled Masses": American Responses to the Indochinese and Syrian Refugee Crises
Bibliographic record
Abstract
In 2015, in the midst of the European migrant crisis, the United States admitted 10,000 Syrian refugees.This was but a miniscule portion of the 4.9 million refugees who had been displaced by the war in the Syrian Arab Republic by the end of that year, and paled in comparison to the efforts of many European nations.That the U.S. commitment to receive and resettle Syrian refugees in 2015 was so small, and that even this low figure served to attract substantial criticism and dismay, is indicative of the divisive nature of the issue of refugee resettlement in the United States.This attitude of reluctance and even animosity toward refugee resettlement is stark in contrast to the expansive American commitment to refugees forty years prior during the height of the Indochinese refugee crisis when, between fall 1978 and the end of 1980, over 166,000 refugees from Vietnam, Laos, and Cambodia entered the United States.This study examines the discourses surrounding refugee resettlement in the United States during the Indochinese refugee crisis of the late 1970s and the ongoing European migrant crisis, with a focus on how the political context of these crises shaped the response of the American government and public.Ultimately, this research demonstrates how foreign policy concerns, domestic political culture, and conceptions of American identity all contribute to determining the extent to which Americans welcome or reject the world's refugees in times of crisis.On November 9, 2016, U.S. presidential candidates Donald Trump and Hillary Clinton met in the second presidential debate of the year's election.When asked about his proposal to ban Muslims from entering the United States, Trump turned to the European migrant crisis."They're coming in by the tens of thousands because of Barack Obama," he declared, "and Hillary Clinton wants to allow a 550 percent increase over Obama."The danger, Trump claimed, was that "people are coming into our country, like we have no idea who they are, where they're from, what their feeling about our country is, and she wants 550 percent more."By Trump's interpretation, the "hundreds of thousands of people coming in from Syria" were in fact "the greatest Trojan horse of all time."Clinton countered Trump's security concerns by affirming that she would "not let anyone into our country that I think poses a risk to us."She further invoked a
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.010 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.006 |
| 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".