Surrogacy Legislation and Kenya's ART Bill 2019: Reproductive Uhuru (Freedom) A Myth or a Reality for Infertile Citizens?
Bibliographic record
Abstract
In 2014, Kenyan parliamentarian Odhiambo Millie MP tabled the Assisted Reproductive Technology (ART) Bill [2019] to regulate assisted reproduction. The Bill restricts surrogacy to married couples only, prohibits payment to surrogates and makes no provision for surrogacy services or its oversight. It is modelled on the United Kingdom's surrogacy laws, although this article confirms the UK's surrogacy laws were intended to discourage surrogacy in the first place, and a Law Commission review shall be published in 2022. In 2007, Thiankolu Muthomi called for Kenyan-designed ART legislation. Kenya's customary woman-to-woman marriage is examined as a taking-off point for technologising Kenya's surrogacy services. The woman-to-woman marriage was constitutionally protected in 2010 and embedded by the enactment of the Protection of Traditional Knowledge and Cultural Expressions Act No. 33 [2016] that promotes the right to cultural expression. This cultural reality should provide the launching pad for a more permissive and auditable surrogacy legislation in Kenya and transferability to sub-Saharan Africa burdened, with the exception of South Africa, by unregulated ART practice.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.018 | 0.011 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".