Bibliographic record
Abstract
This article examines how the shifts in vernacular radio narratives influenced intergroup relations during the 2007-08 electoral violence in Kenya.Using media as an analytical framework, together with original in-depth interview data collected over four months of fieldwork in 2010, the article explores how vernacular radio listeners in Kisumu, Eldoret, and Nyeri interpreted the 2007-08 electoral violence prior to, during, and after the event.It argues that the framing of electoral stakes and subsequent violence by vernacular radio stations is mainly between differentiated and concerted frames, depending on the stage at which the violence manifests itself.Differentiated frames reinforce divisive and/or rebellious attitudes, and are likely to increase intergroup competition and further violence along ethnic lines.Concerted framing underpins the perceived areas of common interest believed to transcend disparate group allegiances, and this establishes the possibility of intergroup dialogue and collaborative attitudes.These findings also highlight the central role of ethno-linguistic proximity and ethno-regional polity as potential drivers of vernacular radio frames, particularly in situations of electoral violence.
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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 | 0.001 | 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 | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".