Limits to Secrecy: What are the Communications Security Establishment's (CSE) Capabilities for Intercepting Canadians’ Internet Communications?
Bibliographic record
Abstract
This chapter contributes to the growing debate in Canada over mass state surveillance by shedding light on key aspects of Canada’s Communications Security Establishment (CSE) domestic internet surveillance capabilities and activities. Drawing mainly on the Snowden documents, it argues that there are good reasons to suspect that the CSE is routinely intercepting the internet communications of millions of Canadians. It relies on an exploratory analysis of Canadian internet traceroute data to estimate where and with which carriers the CSE is most likely to capture internet traffic. This analysis shows that by accessing the main switching centres of a handful of leading telecom providers (e.g. Bell, Rogers, Shaw, Telus) the CSE could surveil a large fraction of Canadians’ internet communications by establishing interception facilities within a few key cities (notably Toronto, Montreal and Vancouver). This chapter draws attention as well to CSE’s excessive secrecy about its domestic internet surveillance capabilities. It concludes by arguing that for the CSE to meet its obligations to respect international human rights and democratic norms, it must reform its practices of excessive secrecy and become significantly more transparent and accountable to Canadians, especially around its capabilities for mass interception of internet communications.
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How this classification was reachedexpand
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".