Turkish Televisual Landscape and Domestic TV Fiction
Bibliographic record
Abstract
In the new multi-channel television environment which stili appears as an unsettled landscape, issues of increasing domestic contents always became a crucial consideration. In Turkey, beginnlng with the first quarter of the 1990's, commercial television has drastically increased the need for television programs like elsewhere in Europe. During the years, what comes out clearly, however, is Turkish television is able to offer a large number of domestic television programs, especially domestic television fiction. Today, in contrast to the case with many European countries, television fiction is overwhelmingly Turkish in Turkey. In fact, foreign penetration had never been a serious threat for the Turkish television market. However, it must be added that a large of domestic programme neither always indicates a diversity of content nor a creative industry. In this context, this paper will summarise the findings of a research that focuses on productive activity and capacity of Turkish broadcasters regarding domestic television fiction. The study also seeks to come to a general understanding of recent developments and new trends in Turkish televisual landscape.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".