Limits to Secrecy: Where Does the CSE Intercept Canadians’ Internet Communications?
Bibliographic record
Abstract
This preview chapter seeks to contribute 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 activities. Drawing mainly on the Snowden documents, it argues that there are good reasons to suspect that CSE is routinely intercepting the internet communications of millions of Canadians. A further exploratory analysis of Canadian internet traceroute data estimates where and with which carriers 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) 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 and concludes by calling on CSE to meet its obligations to respect human rights and democratic norms by being more transparent and accountable to Canadians.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.021 | 0.012 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".