“I Don't Really Agree With That:” Canadians' Perspectives on the 14‐Day Rule in Relation to Artificial Womb Technology
Bibliographic record
Abstract
INTRODUCTION: Complete ectogenesis through artificial womb technology (AWT) would enable fertilization, embryonic development, and fetal development outside of the human body. In 2004, Canada's Assisted Human Reproduction Act established a 14-day legal limit on the in vitro cultivation of human embryos, stymying the domestic development of AWT. Given recent scientific advancements, we aimed to explore Canadians' perspectives on the 14-day rule and AWT development. METHODS: In September 2020-February 2021, we conducted an online English-French survey and semi-structured in-depth interviews with a subset of respondents to solicit Canadian citizens' perspectives on AWT. We audio-recorded and transcribed the telephone/Zoom/Skype interviews and used ATLAS.ti to manage our data. We analyzed survey data using descriptive statistics and interviews for content and themes using inductive and deductive techniques. RESULTS: We received 343 completed surveys and conducted 41 interviews. Although overall knowledge of AWT, in general, and the 14-day rule, in particular, was limited, our participants felt that AWT had the potential to improve lives. Participants also perceived the 14-day rule as an outdated limitation on technological progress and a barrier to AWT development. Participants suggested revisiting the legislation and emphasized centering science, technology, and medicine in any update. DISCUSSION: In 2021, the International Society for Stem Cell Research released updated guidelines which recommended relaxing the 14-day rule, depending on the research objectives. Given the changing domestic and international landscape, Canadian policymakers should revisit the 14-day rule limit imposed by the Assisted Human Reproduction Act and seek input from Canadians when embarking on this reform process.
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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.039 | 0.019 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".