Bibliographic record
Abstract
How does a free press resist state biopower? This article studies the development and dissemination of KANERE Free Press, a refugee-run news source operating in the Kakuma Refugee Camp, that was founded to create “a more open society in refugee camps and to develop a platform for fair public debate on refugee affairs” (KANERE Vision Statement). The analysis of KANERE and its impact on the political subjectivity of refugees living in Kakuma is framed by Foucault’s theory of biopower, the state-sanctioned right to “make live or let die” in its management of human populations. The author demonstrates the force relations between KANERE, its host country of Kenya, and the UNHCR through two ongoing stories covered by KANERE: the broad rejection of the MixMe nutritional supplement and the expressed disdain for the camp’s World Refugees Day celebration. Using ethnographic and decolonizing methodologies, the author privileges the voices and perspectives of the KANERE editors and the Kakuma residents they interviewed in order to provide a ground-level view of refugee’s lived experiences in Kakuma. As KANERE records refugees’ experiences of life in the camp, they construct a narrative community that is simultaneously produced by and resistant to the regulations and control of camp administration and state sovereignty. In doing so, KANERE creates a transgressive space that reaches beyond the confines of the camp.
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 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 | 0.024 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.022 | 0.053 |
| Scholarly communication | 0.047 | 0.039 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.015 | 0.014 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".