Bibliographic record
Abstract
Abstract Natural and physical sciences are based on determinable facts. What is ethical, as distinct from illegal, is largely a matter of opinion. Scientific and industrial activities related to ancient and modern biotechnologies are among the most critically scrutinised for ethical probity by social activists and journalists. The practices and products of biotechnologies should be judged both deontologically – by motivation and intention, and teleologically – by determinable consequence. Bioethical criteria have been proposed by governments, medical practitioners and philosophers for many centuries. During the past decade, various scientifically competent organisations, national and international, have formulated comprehensive protocols by which to determine effectiveness and safety of novel foods, pharmaceuticals and other biologicals, including those derived from genetically modified organisms. Means and opportunities by which to satisfy the health and nutritional needs of impoverished nations and communities differ significantly from those who enjoy greater affluence. It is distinctly unethical for Europeans and North Americans, whose food and health securities are not at risk, to impose their ethical predilections on poorer nations. Equally reprehensible are the diverse tariff and non‐tariff barriers to equitable international trade, and acts of biopiracy inflicted upon poorer nations. As a wise Asian sage has observed, the planet's resources and scientific ingenuity are sufficient to satisfy everyone's need, but not everyone's greed. Present and predictable world‐wide demand for bioscientists and bioengineers exceeds best estimates of supply. Systematically planned, long‐term investments by governments and bioindustries to generate adequate qualified men and women are urgently needed. © 2002 Society of Chemical Industry.
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 | 0.049 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.064 |
| Scholarly communication | 0.022 | 0.012 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.027 | 0.019 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".