Bibliographic record
Abstract
For a brief period following the collapse of the Soviet Union, a degree of political freedom existed in Russia that allowed political satire to appear on television. Different oligarchs purchased important television channels and used them to push the Boris Yeltsin government to approve policies favorable to their business interests by polarizing public opinion against the government. The fractious nature of Russian media in the 1990s and the battles for influence between different oligarchs created an environment in which political satire existed openly in Russian culture, which had not been permitted during the nearly seventy years of communist rule. A particularly significant example of this was NTV’s program Kukli (Puppets) (1994-2002) based on the UK program Spitting Image, which featured puppet versions of prominent Russian politicians, and aired three-hundred-sixty-three episodes. Yeltsin unexpectedly resigned as president of Russia on December 31, 1999, and was succeeded by Vladimir Putin, who has remained the central political figure in Russia since then. Putin’s government almost immediately began to reign in media freedoms. By the end of 2002, all of Russia’s major media properties were under the control of either a state-owned company or close allies of the Russian government. Unsurprisingly Kukli was taken off the air that year, and political satire disappeared from Russian mass culture. This paper will map out the development of Russian satire on television since the collapse of the Soviet Union. Using prominent examples from unscripted standup comedy, evening variety shows and scripted dramas that are openly political and apparently apolitical, this paper argues the Russian television industry engages with and subverts the potential of various satirical genres resulting in the creation of cynical distance that potentially impedes the ability of satire to speak truth to power.
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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 | 0.020 | 0.021 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".