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Record W2462985435 · doi:10.1177/1206331216643779

Refugee Housing Without Exception

2016· article· en· W2462985435 on OpenAlexaff
Kai Wood Mah, Patrick Lynn Rivers

Bibliographic record

VenueSpace and Culture · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsLaurentian University
Fundersnot available
KeywordsRefugeeCitizenshipScholarshipGovernment (linguistics)ColonialismPolitical sciencePower (physics)Construct (python library)PoliticsRacismGender studiesEconomic growthSociologyDevelopment economicsLaw

Abstract

fetched live from OpenAlex

South Africa experienced a recent wave of xenophobic violence in April 2015. Those fomenting violence were mostly Black Africans with South African citizenship targeting Africans from other parts of the continent. Between these attacks, and highly publicized attacks in 2008, South Africa’s government secretly devised plans to construct “model” camps to house migrants with refugee status and those seeking refugee status. The article seeks to understand the space of exception created by government’s proposal considering South Africa’s colonial and apartheid past. This is done by firstly contextualizing the South African case, secondly, placing this South African case within existing scholarship, and thirdly, problematizing the government’s “model.” Beyond this, though, the article presents a conceptual camp design as counterproposal which highlights the power of design to negate spatial exception.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0080.007
Scholarly communication0.0030.002
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.002

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 head0.034
GPT teacher head0.397
Teacher spread0.363 · 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 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

Citations4
Published2016
Admission routes1
Has abstractyes

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