Canada Update: Recent Changes to Canada's Immigration Laws; R v/ Prokofiew: Are Fundamental Rights Really Fundamental Rights; Canada v. GlaxoSmithKline Inc.: Transfer Pricing Agreements
Bibliographic record
Abstract
THIS article begins by briefly considering some of the recent changes to Canada's immigration laws and their collateral effects.Next, the case of R. v. Prokofiew is discussed.This recent case involves an accused's fundamental right to silence.Lastly, through the lens of Canada v. GlaxoSmithKline, the problematic gray area created by the current regulations on transfer pricing will be addressed. I. RECENT CHANGES TO CANADA'S IMMIGRATION LAWSOn June 29, 2012, numerous changes to Canada's Immigration and Refugee system were passed and received Royal Assent.'The changes include provisions designed to stop foreign criminals and human traffickers from abusing Canada's immigration system and to expedite the refugee claim process. 2 Many of these changes focus on reducing the timeline on several components of the immigration system.3 The goal of the changes is ensure that Canada has a "fair and generous" immigration and refugee program, while at the same time ensuring "the safety and security of Canadians will be protected."4 While the goal of these changes is noble and necessary, there are some collateral effects.For example, tougher conditions, like a two-year co-
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.027 | 0.004 |
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".