Variations and voids: the regulation of human cloning around the world
Bibliographic record
Abstract
BACKGROUND: No two countries have adopted identical regulatory measures on cloning. Understanding the complexity of these regulatory variations is essential. It highlights the challenges associated with the regulation of a controversial and rapidly evolving area of science and sheds light on a regulatory framework that can accommodate this reality. METHODS: Using the most reliable information available, we have performed a survey of the regulatory position of thirty countries around the world regarding the creation and use of cloned embryos (see Table 1). We have relied on original and translated legislation, as well as published sources and personal communications. We have examined the regulation of both reproductive cloning (RC) and non-reproductive cloning (NRC). RESULTS: While most of the countries studied have enacted national legislation, the absence of legislation in seven of these countries should not be equated with the absence of regulation. Senator Morin was not correct in stating that the majority of recent legislation bans both RC and NRC. Recent regulatory moves are united only with regard to the banning of RC. While NRC is not permitted in seventeen of the countries examined, it could be permitted in up to thirteen countries. CONCLUSIONS: There is little consensus on the various approaches to cloning laws and policies, and the regulatory position in many countries remains uncertain.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".