Fifth-Dimensional Warfare and National Security in Canada: Situating Microdeviation Theory Within C-59: An Act Respecting National Security Matters
Bibliographic record
Abstract
In an era of rapid technological change, the growing threat environment in the cyber dimension will continue to influence how a sovereign nation contends with attacks that can occur from any corner of the world. The growing adaptation and expansion of technology belonging to the Internet of Things (IoT) and the increasing prevalence of social media (Facebook, Twitter) has also influenced the spreading of attack surfaces that can become victim to exploitation by motivated parties including foreign states and terrorist groups. Against this backdrop, Canada’s own efforts to modernize and reinforce its own national security agencies resulted in the developing and royal assent of 2017’s Bill C-59: An Act Respecting National Security Matters. The royal assent of C-59 poses a unique opportunity to examine the underlying narratives and evidence used by expert witnesses and committee members alike to frame the threat that the cyber environment has when influencing C-59’s more controversial measures. This includes the expansion of the Communication Security Establishment’s (CSE) traditional 3-part mandate to include the use of cyberoperations, or the expansion of Canada’s nation security agencies to utilize the loosely defined “public datasets” despite concerns of possible misappropriation. Utilizing Popham’s (2018) Theory of Microdeviation, this thesis highlights the normalized experiences of Canadians online when considering the exploitation of IoT technology and social media to conduct attacks or sabotage against democratic states, and how these narratives were often used to advance C59’s modernization push. Finally, this thesis also analyzes the implications of C-59 when considering the international community as it relates to a growing cyber arms race akin to 20th century Cold War fears, and how Microdeviation Theory has utility when examining the goals of legislation seeking to control deviant behaviour online.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.054 | 0.060 |
| Scholarly communication | 0.019 | 0.005 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".