Transnational Europe: TV-drama, co-production networks and mediated cultural encounters
Bibliographic record
Abstract
Abstract This article deals with the social and cultural dimensions of globalization and uses both qualitative and quantitative methods to analyse the effects of stronger European integration on media production and reception. It combines theories and methods from sociology, anthropology and media studies and looks at the impact of TV drama genres on the forming of social imaginaries. The article examines structural changes in production and distribution in the European TV-drama landscape since 2000. On the basis of empirical evidence it is argued that a creative, transnational European network of co-productions has increased the distribution of original and often local stories in Europe. The article analyses examples of some successful European drama series, their audiences and reception. The analysis is discussed in the context of national and transnational media policy and the impact of globalisation. Concepts like “imagined community”, “social imaginary”, “banal nationalism”, and “mediated cultural encounters” are connected to the theory of cultural globalisation. Also touched upon are studies of a European civic and cultural identity next to the national, and the role of media and cultural policy in this development. The article concludes that encounters of the kind we find in different forms of TV drama will make Europe more diverse and richer for a much broader audience. The interaction between the particular and universal in “narratives” on our past and contemporary social and cultural order contribute to a better feeling for and understanding of the “us” and “them” in European culture.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".