The Situation of Foreign Satellite TV Channels1 in Iran: A Research in Ardabil Province
Bibliographic record
Abstract
Iran is a multi-ethnic society with a variety of cultures and languages, but Iranian radio and television are state-owned, and their national networks broadcast all programs in Persian which is a limitation within a diverse society. This paper discusses the popularity of satellite TV viewing among Azerbaijani Iranians in the north-western province of Ardabil. The Ardabil region shares borders with Turkey and the former Soviet Republic of Azerbaijan and audiences view satellite broadcasts from these countries. The purpose of this paper is to identify the primary reasons for the use of Turkish and Azerbaijani TV channels by the people of Ardebil. It is hypothesized that Ardabil audience preferences are based on the common culture and language between Turkey, Republic of Azerbaijan and Iran’s Azerbaijan region. A survey conducted by the author indicates that 68 percent of owners point their satellite dishes toward the Turkish satellite; more than 94 percent of the viewers with satellite TV choose Turkey and Azerbaijani channels; and 57 percent of them spend more than three hours per day watching these programs. Nearly 70 percent of the viewers said that if a Turkish channel was established in Iran, they would watch. In addition, 65 percent declared that common cultural ties influence their choice of channels.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 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".