BUILDING INTERNATIONAL APPROACHES TO CLIMATE CHANGE, DISASTERS, AND DISPLACEMENT
Bibliographic record
Abstract
On average, one person is displaced each second by a disaster-related hazard. Most people move within their own countries, but some are forced across international borders. This article outlines the scope of existing international legal frameworks to assist people displaced in the context of disasters and climate change, and suggests a variety of different tools that are required to address the phenomenon. Legal, policy, technical and scientific interventions, including disaster risk reduction, climate change adaptation and mitigation, development, and migration opportunities, will determine whether, and for how long, people can remain in their homes, and whether doing so enables them to lead dignified lives or exposes them to risks and increased vulnerability. Identifying the need for a broad, complementary set of policy strategies necessarily affects how international law should be progressively developed in this area.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.023 |
| Scholarly communication | 0.012 | 0.017 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.014 | 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".