Legal Implications Triggered by an Internet User’s Death: Reconciling Legislative and Online Contract Approaches in Canada
Bibliographic record
Abstract
As significant parts of our lives now take place in the virtual realm, many Canadians will leave behind a trail of digital data upon their deaths. This raises questions as to how to protect a deceased Internet user’s privacy, while also accounting for efficient estate administration of digital assets where such assets are valuable for heirs. Clarity as to what happens to such data upon death is lacking in Canada. In the absence of legislative guidance, online terms of service agreements often determine the fate of our digital data. The author argues that a combined approach of both statutory intervention and strengthened digital service provider policies would be beneficial to protect the interests triggered by an Internet user’s death. Legislative default rules should provide a baseline protection balancing post-mortem privacy and fiduciary access to digital assets. Online tools designed to give the account holder greater control over the fate of one’s digital assets, rather than imposing unilateral terms, should also enhance legislative rules by acknowledging that different types of digital data require bespoke legal treatment.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".