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The politics of protection: aid, human rights discourse, and power relations in Kyaka II settlement, Uganda

2009· article· en· W2135729763 on OpenAlexaff
Christina Clark‐Kazak

Bibliographic record

VenueDisasters · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsYork University
FundersUniversity of Oxford
KeywordsRefugeeSettlement (finance)Government (linguistics)Human rightsChild protectionPoliticsEthnographyPolitical sciencePower (physics)Public administrationEconomic growthSociologyLawBusinessEconomics

Abstract

fetched live from OpenAlex

This paper explores the conceptualisation and application of 'protection' by the United Nations High Commissioner (UNHCR), Ugandan government, and Congolese refugees in Kyaka II refugee settlement, Uganda. Analysing the origins and consequences of a demonstration against school fees, and drawing on other ethnographic data, it explores how different interpretations of this incident reflect different conceptions of, and approaches to, protection. Ugandan government officials viewed the demonstration as a security incident; Congolese and Ugandan adults responded with increased monitoring and 'sheltering' of children and young people; students justified the demonstration as a legitimate manifestation of their rights; while UNHCR promoted assistance and resettlement. The paper argues that prevailing protection responses, including 'sensitisation', sheltering, and resettlement, are de-contextualised from daily realities and fail to address the underlying power relations that undermine protection. It concludes with recommendations on how international refugee agencies can reorient assistance to address protection concerns in refugee contexts.

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)0.005
metaresearch head score (Gemma)0.007
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 score0.019
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0190.031
Scholarly communication0.0100.006
Open science0.0010.010
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.312
Teacher spread0.297 · 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

Citations14
Published2009
Admission routes1
Has abstractyes

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