The Image of the Czech Agriculture Based on the National Television News in the Period of Adaptation of Czechia Into the European Union: Regional Perspectives
Bibliographic record
Abstract
Abstract Agriculture represents one of the most important economic activities that co-creates the qualities of landscapes. While topics such as food production, land utilization, or the development of rural regions are typically taken into account when analysing agriculture, regionally differentiated media portrayals of agriculture constitute a largely innovative approach. The main objective of this paper is to analyse and interpret agriculture-oriented news about individual self-governing regions in Czechia that were broadcasted in the framework of the national TV reporting. The paper is conceived as a historical study of the creation of the image of agriculture in the period from 2004 to 2011, which we define as the period of adaptation of Czech agriculture to the EU. The article includes both quantitative and qualitative dimensions. In summary, the media portrayals of agriculture largely differ from real conditions in Czech self-governing regions. Important themes, such as common agricultural policy or organic farming, have been mostly ignored within regionally focused national TV coverage. On the contrary, TV news is typically focused on one or a few phenomena of unusual or negative character, which is consistent with the gatekeeping conception.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".