Bibliographic record
Abstract
Abstract The following paper discusses the importance of establishing communication channels between academia, the media, and the public with respect to the development of biotechnology within Sub‐Saharan Africa. Citing evidence from interviews with specialists in genetic science, science journalism and public education, the paper reflects on the problems associated with developing multidisciplinary discussion within academic circles, communication between natural scientists and the media, and ultimately the exchange of knowledge between science and society. The major findings from these interviews is that while there is a shared objective and realisation that science communication is important for the development of the region, this objective is hampered by a lack of understanding and trust between scientists and the scientific media. A pattern of mistrust has developed whereby local experts tend to talk to journalists from outside the region rather than from Africa. As a result, there is little opportunity for scientists and the media to communicate the relevance of genetics and biotechnology for the region's development. By way of conclusion, the paper discusses the positive indicators for science communication across the region, based on demand for knowledge, empowerment of scientists and the public, and the urgency of the regional food crisis. Copyright © 2010 John Wiley & Sons, Ltd.
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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.022 | 0.011 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".