Shielding the Public Interest: What Canada Can Learn from the United States in the Wake of <em>National Post and Globe & Mail</em>
Bibliographic record
Abstract
In Canada and the United States, freedom of the press is among the most fundamental rights of citizens; yet, the exact contours of this freedom are still hotly debated. One contested question concerns the right of a journalist to protect the identity of his or her confidential sources. In Canada, two recent Supreme Court decisions established that a journalist may have a privilege to protect the identity of his or her confidential sources. This Note argues that the case-by-case determination with a presumption in favor of disclosure that these two cases establish is insufficient to protect the strong interest in a free press, which is bolstered by the ability to use confidential sources. Rather, Canada should legislatively enact a shield law based on those of many U.S. states in which the privilege is extended broadly and is nearly absolute, with only limited circumstances in which the state can compel disclosure.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.025 | 0.029 |
| Scholarly communication | 0.024 | 0.013 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.018 | 0.020 |
| Insufficient payload (model declined to judge) | 0.007 | 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".