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Record W4412998816 · doi:10.1080/08865655.2025.2539974

Contextualizing Anti-Migrant Sentiment: A Comparative Ethnography of Lesvos and Samos, Greece

2025· article· en· W4412998816 on OpenAlexvenueno aff
Theodoros Kouros

Bibliographic record

VenueJournal of Borderlands Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
FundersResearch and Innovation Foundation
KeywordsEthnographyPolitical scienceHistorySociologyAnthropology

Abstract

fetched live from OpenAlex

This article offers a comparative ethnographic analysis of anti-migrant mobilizations on the Greek Aegean islands of Lesvos and Samos between 2018 and 2022. While both islands experienced intensified border securitization, refugee containment, and NGO activity following the EU–Turkey Deal, their local responses diverged markedly. Lesvos became a site of organized and visible vigilante violence, in contrast to Samos, where little comparable turmoil occurred, and where unrest was characterized by informal exclusion and ambient hostility. Drawing on ten months of ethnographic fieldwork, this study argues that migration pressures alone cannot explain these divergent patterns. Instead, they reflect the interplay of geography, community scale, far-right mobilization, and state complicity. Vigilantism, the paper suggests, should be understood not as a rupture in the rule of law, but as part of a broader moral and spatial infrastructure of border governance, one that operates through both action and silence. By tracing how proximity, reputation, and visibility shape the moral economies of violence and restraint, the article contributes to debates on migration, vigilantism, and the affective politics of European borderlands.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.244
Threshold uncertainty score0.361

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 studies0.0000.000
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 head0.057
GPT teacher head0.393
Teacher spread0.336 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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