Foetal tissue transplantation, the ethics, the law and the born alive rule in Canada
Bibliographic record
Abstract
The advent of antibiotics revolutionized infection management regimes. However, even penicillin was treated with understandable scepticism. Today, its use is common. Foetal tissue transplantation may be the "penicillin" of Parkinson's Disease reatment. It can be transplanted into the recipient and produce the missing chemicals that cause the symptoms. It seems like a clear "go forward" proposition but the fact that foetuses are the tissue source has created social resistance. The foetus is unlike any other human tissue. If separated from the pregnant woman prior to viability, it cannot survive. However, if left alone, it has the potential to develop into an independent and unique human being. Bearing this in mind, how can abortion and transplantation be justified? In true Canadian style, a balance has been reached. First trimester abortions can be obtained electively. Only first and early second trimester foetal tissue is transplantable. I believe that transplantation is not dependent upon the morality of abortion because abortion and suitable tissue both exist. In this thesis, I discuss the various ethical arguments and the legal issues raised by this technology. To put it all into perspective, I review the born alive rule in depth and examine its influence in the law generally. After conducting the foregoing analysis, I support the use of first trimester electively aborted foetal tissue for therapeutic transplantation, with appropriate controls to ensure that the pregnant woman is a willing participant with full knowledge of the ultimate of her foetal tissue.
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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.031 | 0.017 |
| Scholarly communication | 0.015 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".