Confidential Information and Privacy Related Law in Canada and in International Instruments
Bibliographic record
Abstract
Canadians like to think their country is law-abiding and honours its international commitments. Is Our House in Order? explores this public perception while considering whether or not it is correct in terms of domestic law.Examining a range of topics such as treaty implementation, federal-provincial relations, the environment, international humanitarian law, and the protection of confidential information, contributors disentangle the complex processes involved in implementing international law in Canadian law. They highlight how the federal negotiation and ratification process has been opened up to the public, what is being done to give effect to custom in domestic law, and offer suggestions for improving the harmonization of international law implemented at the federal and provincial level.Informative and clarifying, Is Our House in Order? provides well-reasoned prescriptions for improving Canada's implementation of international law and makes a case for thinking about international law as an integral part of Canadian law and society.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.016 | 0.021 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".