When Hackers Strike: The Liability of Reckless Record Holders for Intrusion Upon Seclusion
Bibliographic record
Abstract
Abstract: The Ontario Court of Appeal’s decision in Jones v Tsige established the intentional tort of intrusion upon seclusion, colloquially known as invasion of privacy. Viewed as a powerful tool for the vindication of privacy rights, the tort has become a common cause of action in the class-action context. It has been generally accepted that confidential record holders, like banks and hospitals, will be held vicariously liable for intentional privacy breaches committed by their employees. However, select critics have opposed holding record holders liable when third party hackers gain unauthorized access to confidential records. The resulting gap in privacy right coverage leaves some plaintiffs, who have nonetheless had their privacy violated, without the necessary legal recourse to obtain adequate compensation. To address this gap, we argue in favour of holding record holders liable for intrusion upon seclusion if their reckless conduct contributed to the occurrence of the third party privacy breach.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".