Climate Crisis Induced Migration: A Global Framework to Minimize and Manage Large-Scale Climate Refugees and Migrants
Bibliographic record
Abstract
The ongoing climate crisis will force the migration of up to 1.2 billion people by 2050. Since climate displacement has already begun, having policies in place to mitigate predictable issues that will arise from mass migration and safeguard vulnerable populations is essential. We recommend assigning a special “climate refugee/migrant” status to ensure human rights protections for these refugees/migrants. We also propose preventative measures to help reduce climate-related immigration and essential measures to facilitate refugees adapting to new regions. Finally, we recommend strategies to implement a “Loss and Damage” fund for the developing countries most vulnerable to climate-related disasters. These policies address a critical gap in climate migration policy and could inform the upcoming Conference of the Parties (COP 28) of the United Nations Framework Convention on Climate Change (UNFCCC) in Dubai in November 2023
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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 | 0.015 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".