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Record W1856657616 · doi:10.3138/topia.23-24.100

Fortress Europe: Globalization, Militarization and the Policing of Interior Borderlands

2010· article· en· W1856657616 on OpenAlexvenueno aff
Uli Linke

Bibliographic record

VenueTOPIA Canadian Journal of Cultural Studies · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Security and Public Health
Canadian institutionsnot available
Fundersnot available
KeywordsMilitarizationDehumanizationRacializationCriminologySociologyGender studiesGlobalizationPolitical scienceSecuritizationPower (physics)Political economyPoliticsLawRace (biology)

Abstract

fetched live from OpenAlex

The intensification of militarized violence, racist terror and destructive dehumanization across the globe makes it imperative to examine the corresponding formations of securocratic regimes in the centres of power. With a focus on a united Europe, my essay interrogates the ubiquitous penetration of militarization into everyday life-worlds. My research suggests that in these interior borderlands, emergent cultures of militarization are normalized by recourse to racialization, criminalization and securitization, which in turn gives rise to new intimacies of violence, dehumanization and othering within expanding networks of fortification in a self-proclaimed white society.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.024
Scholarly communication0.0080.004
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.325
Teacher spread0.304 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations23
Published2010
Admission routes1
Has abstractyes

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