The Problem of "Relevance": Intelligence to Evidence Lessons from UK Terrorism Prosecutions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As of November 2017, 60 known foreign terrorist fighters have been permitted to return and live in Canada without criminal consequence.The reason for this, according to the Minister of Public Safety, is the problem of using information collected for intelligence purposes as evidence in criminal proceedings.Often referred to as the "intelligence to evidence" (I2E) dilemma, this challenge has plagued Canada's terrorism prosecutions since the Air India bombing in 1985.Yet, not all countries struggle to bring terrorists to justice.Canada's prosecution statistics pale in comparison to the United Kingdom.In a democracy committed to upholding the rule of law and respecting human rights, prosecuting terrorists is the strongest and most transparent deterrent to this threat.This article argues that as the threat of terrorism grows both domestically and abroad, Canada must learn from the UK's experience and reform the rules of evidence to ensure that criminal charges are pursued.This article will outline and compare the relevant Canadian and UK rules of evidence and assess their practical implications for national security prosecutions in light of primary research conducted in London in the fall of 2017.It concludes with a series of legislative and organizational reforms to improve the efficiency of Canadian terrorism trials.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it