Surfing While Muslim: Privacy, Freedom of Expression & the Unintended Consequences of Cybercrime Legislation
Bibliographic record
Abstract
The Canadian government's Lawful Access discussion paper fails to provide empirical - or anything beyond anecdotal - evidence that the legislative amendments proposed are actually needed. Evidence derived from U.S. law enforcement agencies suggests that technological and administrative impediments - more than legal ones - are the cause of most difficulties experienced in cybercrime investigations and prosecutions, specifically: insufficient basic record keeping by telecommunications and Internet service providers; inability to effect data preservation extraterritorially; inability to circumvent encryption; and, a lack of common data-sharing protocols. Under the guise of international obligations, the government seeks to adopt new legal investigatory tools, the effect of which would be a dilution of judicial oversight for the production of digital data in criminal investigations. These initiatives fail to address the fact that value is inherent in all technology and must be factored into the application of laws which seek to regulate new technologies. Unlike the analog analogue, digital data will often reveal a great deal about one's lifestyle, intimate relations or political or religious opinions. Canadian courts have unequivocally found that information of this nature is subject to the highest constitutional protections, particularly in the criminal investigation context. The Lawful Access consultation paper misinterprets the Supreme Court's standard for finding a reasonable expectation of privacy, by failing to distinguish between the nature of information contained in the various categories of and the label traffic which is otherwise legally meaningless. Traffic data should attract a reasonable expectation of privacy under the Plant doctrine if it passes within the permeable walls of the biographical core or, under the Shearing and Law doctrines, if the owner of the information held a subjective reasonable expectation of privacy in the data, regardless of its content. Such an expectation could flow, inter alia, from the nature of the relationship between a subscriber and a provider. By their nature, packet-mode communication intercepts are liable for massive infringement of third party Charter rights, which the Supreme Court held in Thompson can be determinative of constitutionality. Further, investigatory tools for packet-mode communications cannot separate and content data, necessitating a high reasonable expectation of privacy standard for both. The government's discussion paper claims that production orders - executed by third party telecommunications or Internet service providers - would be less invasive than traditional search warrants. This arguments overemphasizes the physical aspect of a search and fails to recognize that Section 8 of the Charter of Rights and Freedoms protects people, not places or things against unreasonable search and seizures. The history of investigatory detentions under highway safety legislation shows that subjectively-based assessments can too easily mask discriminatory conduct by law enforcement. Contrary to popular understanding, discrimination is a corollary of discretion, not a synonym for racism. It is not a dirty word, but simply an accepted condition that must be factored into the administration of the law. Diluted judicial oversight in the context of cybercrime investigations expands law enforcement and third party discretion to discriminate and could lead to the de facto offences of, for example, surfing while Muslim, or belonging to any negatively-stereotyped group in cyberspace. Applying traditional rules of Lawful Access to the persistent, pervasive and permanent information realm of cyberspace introduces new and unique implications for privacy and freedom of expression. The efficacy of electronic surveillance is such that it has the potential to annihilate any expectation that our communications will remain private. A society which exposes us, at the whim of the state, to the risk of having a permanent electronic recording made of our words every time we send an email or visit a web site might be superbly equipped to fight crime, but would be one in which privacy no longer had any meaning. Consequently, proposed legal solutions to what are often technological or administrative dilemmas may not be the most equitable approach for extending effective policing and intelligence authority to cyberspace. To the extent that governments choose legal tools to investigate and prosecute cybercrimes, great care must be taken that they do not brogate existing constitutional protections.
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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 | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".