Bibliographic record
Abstract
Preface and acknowledgments -- Introduction: the need for cross-cultural perspectives in biotechnology / Michael C. Brannigan -- Pt. I. International overviews and policies -- Ch. 1. Commercialization and benefit sharing of biotechnology: cross- cultural concerns? / Don Chalmers -- Ch. 2. The international human genome project: an overview / Michael J. Morgan and Susan E. Wallace -- Ch. 3. Ethical and legal aspects of biotechnology / Ryuichi Ida -- Pt. II. Specific challenges in cultures and nations - - Ch. 4. The ethics and policy issues in creating a stem cell donor: a case study in reproductive genetics / Jeffrey P. Kahn and Anna C. Mastroianni -- Ch. 5. Optimizing safety and benefits of genetic testing: a look at the Canadian policy / Mylene Deschenes - - Ch. 6. Experimentation on human embryos: the bioethical discussion in Europe with special attention to Austria and Germany / Heinrich Ganthaler -- Ch. 7. The cultural challenge of biotechnology in post-communist Europe / Larissa P. Zhiganova and Yuri M. Gariev -- Ch. 8. Why is this gene different from all other genes? The Jewish approach to biotechnology / Edward Reichman -- Ch. 9. Islamic perspectives on biotechnology / Bushra Mirza -- Ch. 10. Agricultural biotechnology in African countries / Martin O. Makinde -- Ch. 11. Autonomy, humane medicine, and research ethics: an East Asian perspective / David Kum-Wah Chan -- Ch. 12. Indigenous knowledge, patenting, and the biotechnology industry / Stella Gonzalez-Arnal -- Pt. III. Specific global challenges -- Ch. 13. Cross-cultural issues in balancing patent rights and consumer access to biotechnological and pharmaceutical inventions / Dianne Nicol -- Ch. 14. Media, biotechnology, and culture / Margaret Coffey -- Ch. 15. Tricksters, the plague, and mirrors: biotechnology, bioterrorism, and justice / Katharine R. Meacham and Jo Ann T. Croom -- Index -- About the contributors
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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.095 | 0.031 |
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".