From <i>Versailles</i> to <i>No Man’s Land</i> : French broadcasters and the new geopolitical reality of the audiovisual industry
Bibliographic record
Abstract
Based on the examples of Versailles, a series co-produced by Capa Drama with the Quebec company Incendo and Zodiak Fiction for Canal+, and No Man’s Land, a Franco-Belgian-Israeli co-production produced for Arte France and the US platform Hulu, this article aims to compare two different dimensions of the globalisation of the series market and the integration of French producers and broadcasters into this new transnational creative ecosystem. The challenge for the production of Versailles was to bring the French heritage series up to the standards of the English-speaking world while promoting French producers’ financial and artistic creativity in launching series with distinctive stories onto a global market. For No Man’s Land, however, the challenge was to produce a cosmopolitan series, featuring several cultural areas and a multilingual cast. Whether in terms of the broadcasters’ globalisation strategy or in terms of the creative or even cross-cultural challenges raised by the production process, both experiences are representative of the way series are emerging today as a laboratory of audiovisual ‘glocalisation’.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.017 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".