Search and Rescue as an Instrument of Externalisation: A Report from the Central Mediterranean Sea, 2013 to 2017
Bibliographic record
Abstract
The European Union (EU) implemented a maritime interdiction network using search and rescue which interdicted at least 462,813 “illegal migrants” in the Central Mediterranean Sea between 2006 and 2015. This involved 15 discrete, militarised and semi-secret maritime interdiction operations (MIOs) at a minimum cost of 126.9 million 2014 Euros. In this dissertation, I will explore and map these operations and their geographies between 2006 and 2015. First, and based on the given existence of the European Patrols Network, I examine how this network came into being in the first place. This serves to show that the EU purposely created regular maritime interdiction operations using search and rescue to interdict migrants by 2006. This approach also justifies and underpins my subsequent analyses of their histories, functions and outcomes, all of which depend on the network having two specific properties. First: that the EPN was a system intentionally designed to internalise migrants and boa...
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".