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Record W4382790581 · doi:10.1080/08865655.2023.2229846

<i>The Game</i> : Ritualized Exhaustion and Subversion on the Western Balkan Route

2023· article· en· W4382790581 on OpenAlexvenueno aff
Benedetta Zocchi

Bibliographic record

VenueJournal of Borderlands Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
FundersLeverhulme TrustQueen Mary University of London
KeywordsSubversionPoliticsThe ImaginaryAutonomySociologyPolitical economyPolitical scienceLawPsychology

Abstract

fetched live from OpenAlex

The expression to go game is widely used among migrants transiting across the Western Balkan route to describe the attempt to cross a border irregularly. In the Bosnian canton of Una Sana, one of the crucial transit spaces across the route, migrants who go game are repeatedly and violently pushed back from the Croatian side of the border. They return to precarious managed facilities and makeshift camps, where they endure constant evictions, mistreatments, and neglect, while planning their next attempt to cross. This paper takes the vantage point of the game to propose a Bourdieusian reading of exhaustion and subversion on the route. It theorises the game as the sum of ritualised practices (habitus) through which migrants endure and subvert a politics of exhaustion diffusing across EUrope’s transit spaces; and situates it as a collective imperative exemplifying the generative and enduring force of autonomy of migration. Written almost a decade after the year of the so-called migration crisis that opened the political imaginary of the route, this article provides necessary reflections on how dynamics of exhaustion and subversion which developed within EUrope’s border regime sedimented into ritualised and relational practices complicating the already contested geographies of Europe’s transit spaces.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.342
Threshold uncertainty score0.898

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 studies0.0010.000
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 head0.040
GPT teacher head0.346
Teacher spread0.306 · 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 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

Citations10
Published2023
Admission routes1
Has abstractyes

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