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Record W1678395034 · doi:10.25071/1920-7336.40149

Microbuses and Mobile Homemaking in Exile: Sudanese Visiting Strategies in Cairo

2015· article· en· W1678395034 on OpenAlexvenueno aff
Anita Fábos

Bibliographic record

VenueRefuge Canada s Journal on Refuge · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsHomelandRefugeeNegotiationCommissionPoliticsGovernment (linguistics)Ethnic groupPolitical scienceGender studiesEconomic growthSociologyLaw

Abstract

fetched live from OpenAlex

Paying home visits to mark social events and maintain networks is an established cultural pattern in Arab countries. Northern Sudanese displaced in Cairo in the 1990s made significant efforts to continue visiting each other in their temporary homes, despite having to travel long distances to members of their widely scattered networks. The deterioration of the legal and political status of Sudanese living in Egypt during the 1990s contributed to longer-term uncertainty for those who sought safety and security in Cairo. In this article, I argue that this long-term uncertainty constitutes a protracted refugee situation, and that Sudanese visiting practices constituted a mobile homemaking strategy that actively contributed to the negotiation of a complex ethnic identity in their protracted exile. Ranging across space and connecting people through experiences and values of Sudanese “homeyness,” visiting during these fraught years connected individuals and networks into constellations that recreated familiar patterns of homemaking but also encouraged new meanings granted to homeland and belonging. Woven through the more familiar relationship between “home” and “away” were the policy positions about urban refugees taken by the Egyptian government, United Nations High Commission for Refugees, International Organization for Migration, and other humanitarian aid and resettlement agencies, which produced a state-centred view of “home” for Sudanese.

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)0.001
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.982
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.021
GPT teacher head0.308
Teacher spread0.287 · 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

Citations14
Published2015
Admission routes1
Has abstractyes

Explore more

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