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Record W4384007320 · doi:10.1093/jrs/fead040

Capturing the Border in Refugee Solidarity Camp Visits and City Tours in Germany: Theorizing Relationality through the Border as Horizon in Refugee/Migrant Solidarity Activism as Citizenship Politics

2023· article· en· W4384007320 on OpenAlexafffund
Kim Rygiel

Bibliographic record

VenueJournal of Refugee Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsWilfrid Laurier University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSolidarityCitizenshipRefugeePoliticsSociologyGender studiesBorder crossingHorizonPolitical sciencePolitical economyLaw

Abstract

fetched live from OpenAlex

Abstract This article explores the idea of the border as a connective space using the concepts of ‘border’s capture’, ‘borderizations’, and ‘border as horizon’ to highlight ‘practices of relationality’ where borders ‘run the risk of themselves being captured’. This article discusses refugee/migrant solidarity activism as citizenship politics through two examples from Germany across different snapshots in time, illustrating bordering through the camp and the dispersal of borders throughout the city. This article shows why ‘border’s capture’ is central to solidarity mobilizing as citizenship politics, exploring how borders, while integral to violent orderings, are also productive of relations across them in ways that transgress physical and ontological borders of status and belonging. This article argues for conceptualizing the border as horizon to highlight relationality and shows through the two examples why doing so matters politically in terms of how we relate to those identified as ‘outsiders’.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.035

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 studies0.0060.024
Scholarly communication0.0080.008
Open science0.0010.008
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.042
GPT teacher head0.389
Teacher spread0.347 · 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 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

Citations2
Published2023
Admission routes2
Has abstractyes

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