Bibliographic record
Abstract
Science and technology affect everyone on the planet, so, ideally, every country should have a stake in how it develops.Yet people in the so-called Third World lag behind, not only in accessing the benefits of science, but also in access to reliable information about it.Without information, they find it difficult to contribute to the debate.SciDev.net is the Web portal to a free network that is helping to redress the balance by providing authoritative information on those aspects of science that are of most relevance to the developing world.SciDev.netgrew out of a website set up by staff at Nature to cover the World Congress of Science in Budapest in 1999.The full site went live in December 2001, funded by the UK's Department for International Development and the equivalent bodies in Canada and Sweden.It is also sponsored by Nature and Science, and a limited number of articles from these journals are provided each week free of charge.Most members of its board of trustees come from Southern countries; the board also includes the editors of Science and Nature.The main site contains news, features and comment, together with lists of relevant meetings, grant programmes, and job opportunities.There is also a separate regional gateway for each major region: Latin America, the Middle East, South-East Asia and Sub-Saharan Africa.In mid-March 2002, featured news items included a demand from 20 top geneticists for guaranteed free access to the rice genome sequence, and a study of the risk of the simian immunodeficiency virus infecting man.The editorial comment covered the relevance of basic genomics research to developing countries.This information-rich site is a laudable attempt to broaden the perspective of the international scientific community.However, it cannot achieve its full potential until far more of its stakeholders -Third World scientists, students, journalists and administrators -can also benefit from cheap, reliable Internet access.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.454 | 0.452 |
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".