“Refugee Voices,” New Social Media and Politics of Representation: Young Congolese in the Diaspora and Beyond
Bibliographic record
Abstract
This article examines the role of new social media in the articulation and representation of the refugee and diasporic “voice.” The article problematizes the individualist, de-politicized, de-contextualized, and aestheticized representation of refugee/diasporic voices. It argues that new social media enable refugees and diaspora members to exercise agency in managing the creation, production, and dissemination of their voices and to engage in hybrid (on- and offline) activism. These new territories for self-representation challenge our conventional understanding of refugee/diaspora voices. The article is based on research with young Congolese living in the diaspora, and it describes the Geno-cost project created by the Congolese Action Youth Platform (CAYP) and JJ Bola’s spoken-word piece, “Refuge.” The first shows agency in the creation of analytical and activist voices that promote counter-hegemonic narratives of violence in the eastern Democratic Republic of Congo, while the second is an example of aesthetic expressions performed online and offline that reveal agency through authorship and ownership of one’s voice. The examples highlight the role that new social media play in challenging mainstream politics of representation of refugee/diaspora voices.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.000 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".