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Record W4399358643 · doi:10.1080/08865655.2024.2356774

On the Borders of European Pluriversalism. Thinking Europe With/Beyond the Limits of Balibar

2024· article· en· W4399358643 on OpenAlexvenueno aff
Łukasz Moll

Bibliographic record

VenueJournal of Borderlands Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
FundersNarodowym Centrum Nauki
KeywordsPolitical scienceEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

The article aims to initiate a dialogue with Étienne Balibar’s writings on borders, Europe, and universalism, in the context of the contemporary transformations of the borders of Europe and the current crisis of universalist politics. Its first motivation is to demonstrate how Balibar’s work could serve as a theoretical framework for border studies to understand the link between the vacillation of borders and the crisis of European universalism. The figure of boundary, limit, or horizon played a key role in the emancipatory narratives on the idea of Europe. Balibar recognized how the metamorphoses of borders revealed the fundamental aporia of European universalism of any kind: each universalism, no matter how inclusive and radical, has to adopt the particular carrier and designate its limits. Hence the politics of universality tends to be border politics: it rests on constant and infinite transgression of the limits to universalism, without the prospect of overcoming the aporia. The second motivation is to revisit Balibar’s philosophy of borders of Europe by drawing out lessons from contemporary research on border transformations. Answering Balibar’s call to the need to theorize pluriversalism, the article shows how European borders became recently the new sites of pluriversal politics.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.025
Scholarly communication0.0070.009
Open science0.0010.007
Research integrity0.0030.004
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 head0.028
GPT teacher head0.316
Teacher spread0.289 · 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 designTheoretical or conceptual
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

Citations0
Published2024
Admission routes1
Has abstractyes

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