Bibliographic record
Abstract
The courts have treated the unborn child as neither person nor property. Human cloning will challenge this legal principle. Human cloning provides options for future scientific development and treatment of disease and infertility. However, cloning gives rise to issues not yet considered, in law, let alone resolved. These issues are not present in the context of normal human birth. At present, the common law restricts its scope to normal human birth. Does the donor "own" their unborn clone? Who makes decisions on behalf of the unborn clone? The gap between science and law is too large in human cloning research. Law lags behind in adapting to new technologies. This paper will address legal issues in relation to the unborn clone. Cloning will challenge the law in its current state. Decision-making and control of the unborn child are vital issues, to be determined before human cloning can be permitted to take place. The individuals who might have an interest in the unborn clone include the donor, the scientist, who either developed the finished clone or stored the clone prior to implantation, and the surrogate mother. Claims or conflicts might arise in many areas of medicine and law. Does the scientist have an intellectual property right? Can the surrogate mother terminate the pregnancy at will? If the unborn clone is not aborted, what measures are required to protect the fetus? Can the surrogate mother be liable for neglect? Who decides about disclosure of information and knowledge or choice regarding fetal diagnosis and treatment? Who has custody of the unborn clone? In this paper, the concepts of trusts are explored to develop a means of resolving conflicts among the individuals who might claim an interest in the unborn clone. The trust doctrine is flexible and may be useful in resolving claims or conflicts.
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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 | 0.065 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.014 | 0.091 |
| Scholarly communication | 0.028 | 0.071 |
| Open science | 0.005 | 0.019 |
| Research integrity | 0.045 | 0.048 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".