Toward the full and proper implementation of Jordan's Principle: An elusive goal to date
Bibliographic record
Abstract
First Nations children experience service delays, disruptions and denials due to jurisdictional payment disputes within and between federal and provincial/territorial governments. The House of Commons sought to ensure First Nations children could access government services on the same terms as other children when it unanimously passed a private members motion in support of Jordan's Principle in 2007. Jordan's Principle states that when a jurisdictional dispute arises regarding public services for a First Nations child that are otherwise available to other children, the government of first contact pays for the service and addresses payment disputes later. Unfortunately, the federal government adopted a definition of Jordan's Principle that was so narrow (complex medical needs with multiple service providers) that no child ever qualified. This narrow definition has been found to be unlawful by the Federal Court of Canada and the Canadian Human Rights Tribunal. The present commentary describes Jordan's Principle, the legal cases that have considered it and the implications of those decisions for health care providers.
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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 | 0.047 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.053 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.014 | 0.025 |
| Insufficient payload (model declined to judge) | 0.003 | 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".