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Record W2562308999 · doi:10.1080/13621025.2016.1252713

Established and emergent political subjectivities in circular human geographies: transnational Arab activists

2016· article· en· W2562308999 on OpenAlexafffund
Melissa Finn, Bessma Momani

Bibliographic record

VenueCitizenship Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicDiaspora, migration, transnational identity
Canadian institutionsBalsillie School of International AffairsUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCitizenshipPoliticsMiddle EastSociologyPolitical mobilizationLeverage (statistics)Political economyBridging (networking)Gender studiesPolitical scienceLaw

Abstract

fetched live from OpenAlex

In this paper, we argue that Arab transnational citizenship mobilization can be configured through ‘geographies of circularity’ (e.g. bridging multiple locales, encircling the state, transversally stirring political subjectivities, and in the full-circle return of identity). Circularity helps ground and highlight the character and significance of transnational political and social activism, and the transfer of communications, skills, behaviors, organizational forms, tools, and projects (political technologies’) for citizenship. Based on the networks initiated by the Arab revolts, we argue that Arab émigrés, workers, and students – framed here as Arab transnationals – traverse and embody these geographies of circularity and leverage connectivity to mobilize citizenship claims and remit/ bridge/diffuse/export/import important progressive ideas and values locally in the western world and into the Middle East and North Africa (MENA) region.

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)0.004
metaresearch head score (Gemma)0.004
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 score0.007
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0070.022
Scholarly communication0.0060.005
Open science0.0010.007
Research integrity0.0010.002
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 head0.065
GPT teacher head0.356
Teacher spread0.291 · 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

Citations10
Published2016
Admission routes2
Has abstractyes

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