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Record W1922909957 · doi:10.25071/1920-7336.34721

Beyond Basic Education: Exploring Opportunities for Higher Learning in Kenyan Refugee Camps

2012· article· en· W1922909957 on OpenAlexfundvenueno aff
Laura-Ashley Wright, Robyn Plasterer

Bibliographic record

VenueRefuge Canada s Journal on Refuge · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and experiences of immigrants and refugees
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsRefugeeKenyaPolitical scienceEconomic growthPublic relationsRepatriationSociologyLaw

Abstract

fetched live from OpenAlex

This paper seeks to elucidate the socio-cultural and economic benefits of higher education in refugee contexts. NGO and UNHCR initiatives in Dadaab and Kakuma camps are used as a reference point for discussing the challenges, best practices, and potential of higher and adult learning in contexts of protracted exile. This small-scale, qualitative study seeks to understand what opportunities for higher education exist for those living in Kenyan refugee camps, and do existing opportunities yield “social benefits” beyond those accrued by the refugees themselves? Drawing upon interviews with practitioners, observation in schools and learning centres, and data from refugee-service providers, our findings are primarily descriptive in nature and explore the myriad ways in which opportunities for higher learning can strengthen refugee communities in countries of asylum. We contend that although Kenya’s encampment policies limit the potential economic and social benefits of refugee education on a national level, opportunities for refugees to pursue higher education are still immensely valuable in that they bolster refugee service provision in the camps and provide refugees with the skills and knowledge needed to increase the effectiveness of durable solutions at both an individual and societal level, be they repatriation, local integration, or third-country resettlement.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.979
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.090
GPT teacher head0.332
Teacher spread0.242 · 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.

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

Citations94
Published2012
Admission routes2
Has abstractyes

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