Implementing the United Nations global compact on refugees? : global asylum governance and the role of the European Union
Bibliographic record
Abstract
This Policy Brief presents the preliminary findings and policy recommendations emerging from the first 18 months of the ASILE H2020 project (Global Asylum Governance and the EU’s Role). It provides an analysis of asylum governance instruments that have been portrayed as ‘promising practices’ in countries like Brazil, Canada, Jordan, South Africa as well as in the EU. These include instruments like resettlement, community sponsorships, humanitarian admission programmes, and trade deals focused on refugee labour market integration in hosting countries. The Brief highlights that while these instruments present some relevant mobility and inclusionary components, they also display a set of exclusionary features which operationalise hierarchies of deservedness and temporariness. They also lead to discrimination that is incompatible with state commitments under international and regional human rights and rule of law standards. The Policy Brief provides a set of lessons learned in the implementation of the EU’s Pact on Migration and Asylum and the EU’s cooperation with third countries on migration and asylum management in light of the United Nations Global Compact on Refugees.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.003 |
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".