(You're) Having My Baby: Surrogacy Fees as a Cost of Future Care Award in Canadian Tort Law
Bibliographic record
Abstract
In April 2017, the BC Supreme Court released its decision in Wilhelmson v Dumma. After a horrific motor vehicle collision in which she was critically injured, the plaintiff was left unable to bear children. Justice Sharma, in a precedent-setting decision, awarded the plaintiff $100,000 for future surrogacy fees under the head of cost of future care. With this award, Justice Sharma attempted to return the plaintiff as close to her pre-tort position as money could do by giving her back the opportunity to have a biological child. The Wilhelmson decision was groundbreaking in its recognition of the plaintiff’s loss of reproductive capacity as a real, tangible loss deserving of a pecuniary damages award. Historically, the tort system has often undercompensated women for procreative harm and other female-specific injuries, citing moral and policy rationales to justify the departure from ordinary principles of tort law. These arguments and rationales are often based on little more than intuition and hypothetical risks. In order to fully compensate women for their losses, courts may need to critically examine the principles that have often restricted female plaintiffs’ recovery and develop creative remedies as Justice Sharma did with her award of surrogacy fees in Wilhelmson.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.016 | 0.024 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.010 | 0.010 |
| 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".