Bibliographic record
Abstract
BACKGROUND: Debates persist around the world over the development and use of genetically modified organisms (GMO). News media has been shown to both reflect and influence public perceptions of health and science related debates, as well as policy development. To better understand the news coverage of GMOs in China, we analyzed the content of articles in two Chinese newspapers that relate to the development and promotion of genetically modified technologies and GMOs. METHODS: Searching in the Chinese National Knowledge Infrastructure Core Newspaper Database (CNKI-CND), we collected 77 articles, including news reports, comments and notes, published between January 2002 and August 2011 in two of the major Chinese newspapers: People's Daily and Guangming Daily. We examined articles for perspectives that were discussed and/or mentioned regarding GMOs, the risks and benefits of GMOs, and the tone of news articles. RESULTS: The newspaper articles reported on 29 different kinds of GMOs. Compared with the possible risks, the benefits of GMOs were much more frequently discussed in the articles. 48.1% of articles were largely supportive of the GM technology research and development programs and the adoption of GM cottons, while 51.9% of articles were neutral on the subject of GMOs. Risks associated with GMOs were mentioned in the newspaper articles, but none of the articles expressed negative tones in regards to GMOs. CONCLUSION: This study demonstrates that the Chinese print media is largely supportive of GMOs. It also indicates that the print media describes the Chinese government as actively pursuing national GMO research and development programs and the promotion of GM cotton usage. So far, discussion of the risks associated with GMOs is minimal in the news reports. The media, scientists, and the government should work together to ensure that science communication is accurate and balanced.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.014 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".