Watching<i>The Daily Show</i>in Kenya
Bibliographic record
Abstract
Global distribution of a popular American television programme – Jon Stewart's Daily Show – offers a rare opportunity to examine transnational contingencies of meaning in political satire. Drawing on focus group discussions in Kenya, this analysis shows how some East Africans appropriated and reinterpreted – indeed unexpectedly subverted – The Daily Show's political content, deriving from it insights that Stewart himself might have found surprising. Kenyan viewers perceived in The Daily Show gaps between the rhetoric and reality of empire and pointed to limitations of Stewart's dissident satire as they rejected its depictions of non-wealthy nations and marginalized peoples. They reconfigured Daily Show episodes as commentaries on global power relations; reflected critically on Kenyan politics, media and their own political subjectivities; and revised their own earlier assumptions about the gap between Africa and supposedly ‘mature’ democracies such as the United States. Thus, American political satire such as The Daily Show can activate in foreign audiences new perceptions of differences between the ‘West’ and the rest and new forms of political imagination.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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.
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".