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Record W2943917422

The Ship is Not the Only Vessel on the River: Revisiting First Nations' Mobility Rights under Article III of the 1794 Jay Treaty

2019· article· en· W2943917422 on OpenAlexaboutno aff
Amelia Philpott

Bibliographic record

VenueAppeal: Review of Current Law and Law Reform · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Systems and Judicial Processes
Canadian institutionsnot available
Fundersnot available
KeywordsPlaintiffDamagesTortHarmLawSupreme courtEconomic JusticePolitical scienceTreatyCausationLiabilitySociologyLaw and economics
DOInot available

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.888
Threshold uncertainty score0.222

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0060.021
Scholarly communication0.0060.005
Open science0.0020.004
Research integrity0.0100.009
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.025
GPT teacher head0.308
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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