Behind the Screen: The Role of State‐TV Relationships in Russia, 1990–2000*
Bibliographic record
Abstract
Les systèmes de régulation de la production des programmes télévisuels sont aussi importants dans les études des médias que l'analyse du corps d'un texte. l'économie politique rend possible l'étude des programmes télévisuels et des systèmes de régulation de la production télévisuelle dans un seul modèle de même que leurs interconnections. Deux systèmes régulateurs de télévision sont décrits, et les dynamiques de leur transformation sont présentées. Les résultats des entrevues avec les fonctionnaires de l'industrie télévisuelle sont utilisés pour examiner l'influence des relations entre l'État et les entreprises de télévision sur le contenu des programmes produits par la télévision russe entre 1990 et 2000. This paper argues that the content of television programs is influenced by how their production is organized and regulated. The political‐economic approach provides a useful framework to link television programs and the regulation of TV production within a single model, and to investigate their interrelationship. Two systems of TV regulation are described in this paper and their evolution is discussed. Data from in‐depth qualitative interviews with Russian television industry insiders are used to examine the impact of changes in the regulation of television on the types and content of programs produced between 1990 and 2000.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".