It Shouldn’t be Small Potatoes: The Future of Civil Damage Awards under Canada’s Personal Information Protection Legislation. Part Two: Inadequate PIPEDA Damages and the Way Forward
Bibliographic record
Abstract
This is the second part of a two-part article. The first part can be found at 52 Adv Q 427 (2022). The Personal Information Protection and Electronic Document Act (PIPEDA) is well known as federal legislation governing the protection of personal information in the private sector. This article, published over two parts, focusses on a lesser explored but particularly concerning aspect of PIPEDA, namely the low damage awards (averaging between $3,000 to $5,000) granted by courts to applicants who establish a breach of the Act and the low number of actual applications (24 applications in 20 years). Chronically low monetary awards threaten PIPEDA’s legislative objective of recognizing the individual’s right of privacy in their personal information. As the low number of applications reflect, when it makes no economic sense to do so, otherwise deserving complainants will be discouraged from seeking damages or simply driven to pursue solutions such as class actions. PIPEDA’s damage provision thereby stands to wither away from disuse. This article offers a three-fold solution to insufficient quantum and is inspired more generally by the functional approach to monetary damages presented by Justice Cromwell in an Isaac Pitblado lecture. First, damage quanta under PIPEDA must more rigorously reflect the status of personal information protection legislation, including its constitutional overlay and link to what have been termed “dignitary” torts such as the common law privacy torts and defamation. Second, courts should measure quantum based on insights from torts closely related to breach of privacy under PIPEDA which reflect a higher quantum. Third, courts must firmly reject the Federal Court’s 2010 decision in Randall v Nubody’s Fitness Centres which held that damages under PIPEDA are only recoverable in “the most egregious situations.” Egregiousness is not an ingredient required by the Act and wrongly reduces its scope.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.013 |
| Scholarly communication | 0.019 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.012 | 0.009 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".