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Record W4252847468 · doi:10.32920/ryerson.14644611

Kapturing Kakuma : the commodification of refugees and participatory communication alternatives

2021· preprint· en· W4252847468 on OpenAlexafffund
Jacqueline Strecker

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsToronto Metropolitan UniversityCentre for Social InnovationYork UniversityWestern University
FundersYork University
KeywordsRefugeeCommodificationAgency (philosophy)Political scienceGender studiesSyrian refugeesCitizen journalismSociologyLawSocial scienceEconomy

Abstract

fetched live from OpenAlex

Over the past 50 years, the image of statelessness has shifted from heroic European refugees to depictions of nameless, impoverished refugees from the 'Third World'. Although this shift apparently stems from noble intentions, the image of the 'vulnerable refugee' has stripped refugees of agency and expressive rights. The photographs published by The United Nations High Commissioner for Refugees (UNHCR) has employed this vulnerability frame in order to lobby for western aid by presenting an easily digestible discourse, congruent with Western ideology. The UNHCR has thus commodified refugees in order to ensure funding from western donors. This paper challenges this commodification by presenting a comparative analysis of the UNHCR's historical photographs, and images produced through a participatory photography project conducted in the Kenyan Kakuma Refugee Camp. This project shifts the conventional illustrative refugee discourse by identifying and rejecting the political and economic frameworks that have institutionalized the voiceless and commodified refugee.

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)0.008
metaresearch head score (Gemma)0.006
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 score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0190.035
Scholarly communication0.0120.011
Open science0.0010.010
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.075
GPT teacher head0.375
Teacher spread0.300 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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