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Record W4290949179 · doi:10.1080/08865655.2022.2108110

Migration, Borders and “De-bordering” in Pandemic Times: Voices as Interlocution from Quarantine Ships in Italy

2022· article· en· W4290949179 on OpenAlexvenueno aff
Chiara Denaro, Paolo Boccagni

Bibliographic record

VenueJournal of Borderlands Studies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
FundersMinistero dell’Istruzione, dell’Università e della Ricerca
KeywordsIrregular migrationRefugeeEnforcementPandemicQuarantinePolitical scienceVulnerability (computing)MobilitiesDe factoIsolation (microbiology)Coronavirus disease 2019 (COVID-19)GeographySociologyEconomyEconomic geographyLawComputer securityInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

The Covid-19 pandemic has deeply affected the configuration of border regimes worldwide, resulting in further selective restrictions to individual cross border mobilities. The Mediterranean space, where sea-crossings have been a structural part of migration for over two decades, has been targeted by multidimensional and transversal re-bordering policies: from externalization to search and rescue, from asylum to detention. The “unsafe harbour strategy” and the resulting implementation of offshore isolation, de facto detention, on quarantine ships were key components of these re-bordering policies. These strategies have prevented a number of potential refugees from accessing asylum, thereby reinforcing the so-called hotspot approach. Combining traditional qualitative research methods with digital ethnographic research on “quarantine ships” in Italy, this paper explores migrants' reactions and responses to border enforcement via offshore isolation. By focusing on the voices emerging from quarantine ships, and on the subsequent interlocution between different actors and stakeholders, we highlight the emergence of various forms, tools and strategies of debordering. These are the outcome of the ongoing interaction between confined migrants, civil society stakeholders and the “onshore” world. We eventually discuss the implications of these interlocutions for research on the interplay between bordering and de-bordering in migration management and control.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.344
Teacher spread0.322 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2022
Admission routes1
Has abstractyes

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