La agenda medioambiental: el rol de los medios de comunicación en Nicaragua
Bibliographic record
Abstract
The purpose of this paper is to know the media agenda of Nicaraguan television newscasts. For this purpose, it was decided to take as a reference the following newscasts: Crónica TN8 of Canal 8, TV Noticias of Canal 2 and Noticiero Acción 10 of Canal 10. The objective was to reflect on the role played by the television media in environmental coverage. In addition to identify if the informative contents are focused on environmental education, and, finally, to analyze the need for specialized training in environmental journalism, which allows the communicator to address these issues with a more critical and reflective vision oriented to the care of our common home, the Planet Earth. For the development of this paper, a documentary review was carried out, covering the phases of search and compilation of information up to its analysis and interpretation. The sources consulted were scientific articles published in electronic repositories, as well as the monitoring of news programs, considering variables such as: title of the news, content, type of coverage and verification of the same in audiovisual and written format, through the websites of the television media. This was carried out in the first quarter of 2023. The main conclusions point out that there is little interest of the media in promoting among their audiences a culture oriented to conserve and preserve the environment; which could be attributed to three important aspects such as: the lack of knowledge that journalists have on the subject, a second aspect is that this type of content is not considered attractive and therefore does not generate ratings and finally it is not lucrative in terms of sales for the media. It is important to mention that there is a gap in the writing of news content, limited only to the coverage of the event, without providing any informative and preventive value. The lack of educational production, could lead to a false understanding in their audiences that everything is fine, when in fact this articulated work between institutions, private companies and the State is needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".