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Record W4402862156 · doi:10.1177/00207152241274982

Re-education camp as a spatial governance form: Separation, structure, and staging in Rwanda’s <i>ingando</i> camps

2024· article· en· W4402862156 on OpenAlexvenueno aff
Andrea Purdeková

Bibliographic record

VenueInternational Journal of Comparative Sociology · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Geopolitics and Ethnography
Canadian institutionsnot available
Fundersnot available
KeywordsSeparation (statistics)Corporate governanceSociologyPolitical scienceGeographyManagementMathematicsEconomicsStatistics

Abstract

fetched live from OpenAlex

Compared to other forms of encampment, contemporary re-education camps do not draw much comparative work in sociology and politics. Even less is known about the governance of such camps, and the ways in which unique spatial aspects of encampment are meant to facilitate the intended social and ideological transformation which is their hallmark. Taking post-genocide Rwanda’s uniquely widespread system of ingando “solidarity” camps as its case study, this article argues that three aspects of spatial governance in particular—separation, (hyper)structure, and staging—are central to the modus operandi of re-education camp as a technology of transformative power. The ingando system was born amid a crisis of citizenship in the wake of mass atrocity and shaped by a rebel-turned-ruler elite aiming to reconstruct citizenship sifted through the lens of glorified militarism. The ingando camps are not only about learning together, but their remoteness is meant to unsettle, their structure is meant to foster discipline, and their staging and experiential aspects are meant to simulate values of unity as cohesion and submission to a broader goal.

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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.021
GPT teacher head0.390
Teacher spread0.369 · 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 designTheoretical or conceptual
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

Citations1
Published2024
Admission routes1
Has abstractyes

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