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Record W4224013027 · doi:10.1080/08865655.2022.2060281

Kapka Kassabova and Ben Judah: Writing Borders and Borderscapes in Contemporary Europe

2022· article· en· W4224013027 on OpenAlexvenueno aff
Jopi Nyman

Bibliographic record

VenueJournal of Borderlands Studies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsGeopoliticsContext (archaeology)NarrativeBrexitIdentity (music)SociologyEthnic groupReading (process)HistoryAestheticsPolitical scienceAnthropologyLiteratureLawArtPoliticsEuropean union

Abstract

fetched live from OpenAlex

This article addresses the role of border and borderscapes in two contemporary texts by writers based in Britain, Kapka Kassabova’s Border: A Journey to the Edge of Europe [Kassabova, Kapka. 2017. Border: A Journey to the Edge of Europe. London: Granta] and Ben Judah’s This Is London: Life and Death in the World City [Judah, Ben. 2016. This is London: Life and Death in the World City. London: Picador]. Reading these texts as narratives of border in the context of contemporary discourses on Europe and Brexit, the article shows how the texts challenge the general bordering tendency to represent Europe and Europeans as Britain’s Others, marked by difference and ethnic, cultural, and geopolitical borders. Examining the works in the context of the borderscape concept, the article shows how the texts’ border-crossings challenge such binary thinking and offer ways to locate alternatives to simplistic versions of national identity. The article shows a transforming discourse of borders that underlines their porosity and points to the emergence of new identities as the result of border-crossings. The borderscapes examined in the article (Bulgaria’s southern border and London) reveal diverse belongings and becomings in historical and contemporary contexts that generate new identities.

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 score0.491
Threshold uncertainty score0.637

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 head0.044
GPT teacher head0.348
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 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

Citations8
Published2022
Admission routes1
Has abstractyes

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