Refining legal frameworks for cross-border climate-induced displacement: a comprehensive analysis of provisions, definitions, and new arrangements under international law
Bibliographic record
Abstract
The thesis addresses the urgent and growing issue of displacement driven by climate change. As climate impacts intensify, more individuals are forced to cross borders in search of safety, yet current international legal frameworks are ill-equipped to offer them adequate protection. This research critically examines the existing legal provisions within International Refugee Law (IRL) and International Human Rights Law (IHRL), highlighting their limitations in addressing the unique challenges posed by climate-induced displacement. The thesis explores the inadequacies of current refugee definitions under the 1951 Refugee Convention and the challenges in applying non-refoulement protections to those displaced by environmental factors. It also delves into the terminological ambiguities that plague the discourse, proposing a more coherent and inclusive definition that accurately captures the diverse realities of climate-induced displacement. Building on this analysis, the thesis advocates for significant reforms, including the potential for a new international convention specifically designed to address the legal gaps faced by climate refugees. It emphasizes the need for a comprehensive legal framework that includes state responsibility, effective implementation mechanisms, and robust international cooperation to ensure the protection of vulnerable populations affected by climate change. In summary, this thesis contributes to the ongoing global dialogue on climate-induced displacement by offering a critical evaluation of current legal frameworks and proposing actionable reforms to enhance the protection of those displaced across borders due to climate change.
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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 | 0.023 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.009 | 0.042 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.007 |
| 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".