Protecting Human Research Subjects: A Jurisdictional Analysis
Bibliographic record
Abstract
The most recent speech from the throne contained a pledge from the federal government to "work with provinces to implement a national system for the governance of research involving humans, including national research ethics and standards." This commitment signals a desire on the part of the federal government to address concerns about the inadequacies of the current governance of health research involving humans (RIH). To this end, Health Canada's Ethics Division is currently exploring the ways in which such a national governance system for RIH might be implemented. It is important for the federal government, as it moves toward making good on its Throne Speech pledge, to have clarity concerning the jurisdictional authority to legislate with regard to RIH. Specifically, it needs to be clear about whether the constitutional jurisdiction over RIH rests with the federal government, the provinces or whether it is divided or shared between them. The answer to this jurisdictional question will shape the federal government's approach to any negotiations with the provinces concerning the creation and implementation of a national system of governance for RIH. Addressing the jurisdictional issues is an important precursor to any negotiation process for two reasons. First, the scope of federal and provincial power over RIH is key both to the design and implementation of a comprehensive national system of regulation over RIH. It is necessary to determine which sphere of government has the power to do what before deciding how to go about creating a national governance system. Second, knowing the extent and the scope of federal jurisdiction with respect to RIH might strengthen the negotiating position of the federal government vis a vis the provinces. It will provide clarity as to what the federal government could do in terms of regulating RIH if the provinces are unwilling to cooperate. In short, it will make clear whether, and to what extent, the federal government needs provincial agreement to regulate RIH and what options are available to the federal government if such agreement is not attained.
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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 | 0.382 | 0.280 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.017 | 0.072 |
| Scholarly communication | 0.021 | 0.027 |
| Open science | 0.007 | 0.016 |
| Research integrity | 0.020 | 0.023 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".