Bibliographic record
Abstract
Framing, Federalism, and FailureThe world has undergone a revolution in assisted reproduction, as processes such as in vitro fertilization, embryonic screening, and surrogacy have become commonplace.Yet when governments attempt to regulate this field, they have not always been successful.Canada is a case in point: six years after the federal government created comprehensive legislation, the Supreme Court of Canada struck it down for violating provincial authority over health.In Assisted Reproduction Policy in Canada, Dave Snow provides the first historical exploration of Canadian assisted reproduction policy, from the 1989 creation of the Royal Commission on New Reproductive Technologies to the present day.Snow argues the federal government's policy failure can be traced to its contradictory "policy framing," which sent mixed messages about the purposes of the legislation.In light of the federal government's diminished role, Snow examines how other institutions have made policy in this emerging field.He finds provincial governments, medical organizations, and even courts have engaged in considerable policymaking, particularly with respect to surrogacy, parentage, and clinical intervention.The result -a complex field of overlapping and often conflicting policies -paints a fascinating portrait of different political actors and institutions working together.Accessibly written yet comprehensive in scope, Assisted Reproduction Policy in Canada highlights how paying attention to multiple policymakers can improve our knowledge of health-care regulation.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.787 | 0.584 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".