When Secret Intelligence Becomes Evidence: Some Implications of Khadr and Charkaoui II
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
Khadr and Charkaoui II highlighted that the Canadian Security Intelligence Service (“CSIS”) has constitutional and statutory obligations to retain and disclose secret intelligence. Although the two cases were made outside of the criminal context, they, when combined with McNeil, have implications for the retention and disclosure of intelligence in terrorism prosecutions. The two decisions by the Supreme Court of Canada have the potential to subject secret intelligence to the rule of law, external verification and adversarial challenge in legal proceedings.This essay will start with a little history to help appreciate the change that could be triggered by Khadr and Charkaoui II. An overview will be provided on the evolution of Canadian approaches to secrecy and the use of intelligence as evidence. Then the essay will use Khadr to discuss the disclosure of intelligence collected and disseminated by CSIS. Also, the Court’s decision in Charkaoui II with respect to the proper interpretation of section 12 of the CSIS Act will be discussed, focusing on the retention of intelligence collected about individuals and groups. Finally, this paper will examine some possible harms and benefits of the judicialization of intelligence. Judicialization of intelligence and subjecting CSIS to the rule of law can expose errors, exaggerations and speculation in analytical conclusions. Generally, it is a positive development although it is not without its dangers including threats to secrecy and privacy as well as false confidence in the accuracy of intelligence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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