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Record W4282554229 · doi:10.20935/al5393

Search and Rescue as an Instrument of Externalisation: A Report from the Central Mediterranean Sea, 2013 to 2017

2022· article· en· W4282554229 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAcademia Letters · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMaritime Security and History
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsInterdictionSearch and rescueEurosMediterranean seaEuropean unionGeographyComputer scienceMediterranean climateOperations researchEnvironmental resource managementBusinessInternational tradeEngineeringArchaeologyArtificial intelligenceEconomicsHumanities

Abstract

fetched live from OpenAlex

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...

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.508
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.047
GPT teacher head0.315
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it