Perspectives in Dialogue: Debating the GCR’s Impact on the International Refugee Protection Regime
Bibliographic record
Abstract
The State adopted the Global Compact on Refugees (GCR) in 2018 to consolidate the International Refugee Protection Regime (IRPR). Drawing on International Relations (IR) theories and international law, different perspectives can be taken on the nature of the GCR and the IRPR, and their legal and non-legal relationship. The lack of a universally accepted definition for the IRPR allows for various interpretations, ranging from narrow positivism to broad global governance and self-organisation approaches. Similarly, the legal status of the GCR can be seen as non-law, soft law, or fully binding law depending on the criteria used. Applying realist, liberal, and constructivist theories, this article argues that the GCR’s anticipated legal and political development and its impact on the IRPR will be influenced by the chosen IR paradigm, reflecting different views on the rule of international law and power dynamics among stakeholders. By examining the case study of Kenya as a host of a protracted refugee operation, the article provides a practical illustration of how different IR lenses offer divergent perspectives on international burden and responsibility sharing in the Global South. This analysis aims to provide a comprehensive and nuanced understanding of the complex relationship between the GCR and the IRPR.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.030 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.031 | 0.069 |
| Scholarly communication | 0.023 | 0.021 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.015 | 0.018 |
| Insufficient payload (model declined to judge) | 0.005 | 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".