Analyzing the United States’ Limited Response to the Syrian Refugee Crisis
Bibliographic record
Abstract
The Syrian refugee crisis can be described as one of the biggest, if not largest, humanitarian crisis of the 21st century. The crisis is a result of an ongoing civil war between rebel groups and the government forces of the Assad regime. Since the beginning of the war in 2011, over 400,000 have been killed and a combined 11 million have been displaced either internally or externally from their homes (Human Rights Watch, World Report 2018). The United Nations and the international community have openly expressed discontent with the dealings of the Assad regime, and as a result, have attempted to aid this struggling nation ridden with extreme violence. With more than 11 million displaced Syrians seeking refuge in other nation states across the world, various states have provided more lenient measures and policies to offer legal refugee resettlement within their respective borders (Morico 2017). However, the response has differed greatly on a state by state basis, with the United States resettling an inadequate number of Syrian refugees. According to the State Department, near the end of President Obama’s term in 2016, the U.S. had resettled 15,479 Syrian refugees. In 2017, the country let in 3,024. Horrifyingly, the National Public Radio has stated that by April 2018, the United States had only taken in 11 Syrian refugees (Amos 2018). These numbers are close to nothing in the grand scheme of over 11 million refugees displaced worldwide. Meanwhile nation states, such as Germany, Canada, and neighboring states of Turkey, Lebanon, and Jordan, have implemented liberal refugee policies to alleviate the crisis, despite the hardships that resettling thousands, or millions, of refugees would bring to the state. The American response to the severity of the crisis has accomplished little to alleviate the growing issue. Our response is troubling, thus sparking the question why our response to this injustice has been so limited in scope, while other world powers have accepted thousands or millions within their borders. This has created an unnecessarily hard burden on the neighboring countries around Syria, which have struggled to relocate and provide for millions of displaced refugees within their often fragile borders. These nations, including Jordan, Lebanon, and Turkey, do not have the resources and adequate social structures to provide aid for millions, as the United States and other superpowers could do more readily. Furthermore, states and international organizations have responded to the crisis by providing millions in
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".