Bibliographic record
Abstract
War and terror, demographic imbalances, unchecked climate change, and rampant criminality are the drivers of catastrophic migrations. In the first quarter of the twenty-first century, we witnessed the largest number of forcefully displaced human beings in record. Concurrently the world is now facing the largest “crisis of confinement” in history, leaving millions of human beings in search of shelter far away from the high and middle-income countries, lingering in interminable limbo. In the aftermath of World War II, Europe, the United States, and their allies developed policies for forcefully displaced refugees based on the assumption that whatever caused them to flee their homes would be resolved and refugees would return home. These architectures, we argue, are misaligned with the new conditions. Devastated environments in states with weak institutional capacities hold little promise for safe return. A new twenty-first-century cartography of mass migration suggests forms of migration that do not fit existing policy frameworks. First, most forcefully displaced migrants today stay as internally displaced either in their own countries or in camps in neighboring states often in subhuman conditions with few protections. Second, protracted conflicts are sending millions fleeing with no expectation of returning. Third the architectures in place are generally blind to the developmental needs of children. Crying children are the face of the catastrophic migrations of the twenty-first century. Worldwide, one in every two hundred children is a refugee, almost twice the number of a decade ago. In 2017, there were over twenty-eight million children forcefully displaced. For the first time in history, over half of all refugees under the United Nations High Commissioner for Refugees mandate are minors. Even when temporary protection is possible or desirable, children in flight need more than a safe haven. They need a place to grow up. They need the safety of home. In this Introduction we review the best evidence and current thinking on physical health, mental health, and trauma; legal protections; and education for forcefully displaced children and youth.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.518 | 0.340 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".