The Right to Oblivion: Data Retention from Canada to Europe in Three Backward Steps
Bibliographic record
Abstract
The issue of data retention is one that has become prominent in recent times, particularly with the recent extension of Canadian privacy legislation to cover the private sector. This paper investigates the origins of the prohibition on data retention under European and Canadian law and its subsequent development in Europe and Canada with an emphasis on the trends, disparities and other consequences generated by the prohibition since 1968, the date of the first Council of Europe recommendations in relation to data protection in general. In Europe, ever since the first proposal for harmonized data protection laws was made by the Council of Europe in 1973, one of the fundamental principles of data protection law has been that of data retention or data conservation - that is, the obligation of the data user or controller to keep data for a limited period of time only. The 1995 EU Directive on Data Protection contains an express data-retention principle. The OECD Guidelines, which were used to develop Canada's privacy standard and subsequent privacy legislation, are less explicit. In Canada, Part 1 of the Personal Information Protection and Electronic Documents Act (PIPEDA) establishes Principle 5 on data retention or data conservation, which is closely allied with its European counterpart. The connections between each of these discrete legal instruments are obscured by the legal backgrounds to each of PIPEDA and the EU Directive. The paper examines the data-retention principle under PIPEDA, analyzing the extent to which this principle has been influenced by the European legal developments and the extent to which other factors were important in shaping this fundamental rule.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.022 | 0.024 |
| Scholarly communication | 0.023 | 0.013 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.009 | 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".