Safeguarding Confidential News Sources? Assessing the Protections in the Federal Journalistic Sources Protection Act
Bibliographic record
Abstract
The monograph, edited by Dr. Chris Hunt, examines various aspects of the law of privilege in Canada. This book chapter analyzes protections with respect to journalist-source communications in Canadian evidence law. After first explaining the application of the so-called case-by-case privilege to such communications and its limitations, the chapter then focuses attention on the statutory protections set out in the Journalistic Sources Protection Act which amends the Canada Evidence Act. The chapter scrutinizes the new statutory protections and their limitations, in addition to drawing comparisons with similar legislation in New Zealand. This chapter fits into my larger research agenda, which explores the intersections between law and resistance. The form of resistance discussed in this work is the conduct of journalistic sources who disclose confidential information about pressing matters of public concern to journalists. Journalists in turn then reveal the information to the public. Such unauthorized disclosures may relate to and expose the misconduct of public or private actors and consequently challenge their power. Law holds the power to protect and legitimize such resistance. However, this power to protect and legitimize correlates to the scope of journalist-source privilege in any given jurisdiction. In the context of the new statutory protections promulgated by the Canadian Parliament, such prophylaxes are tied to the text, context and purpose of the legislation and the corresponding interpretations courts may articulate.
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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 | 0.033 | 0.123 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.009 | 0.020 |
| Scholarly communication | 0.016 | 0.009 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".