Bibliographic record
Abstract
A study of two cases in which Ontario organizations, the Toronto Transit Commission (TTC) and the Ontario Lottery and Gaming Commission (OLG), attempted, with the support of the Information and Privacy Commissioner at the time, Ann Cavoukian, to design privacy into their use of closed circuit surveillance cameras (CCTV). The study examines the role of the regulator in facilitating Privacy by Design (“PbD”) solutions. With the introduction of PbD into the European Union General Data Protection Regulation (GDPR), it is important to understand the conditions under which PbD can succeed and the role which regulators can play (if at all) in promoting such success. The findings are organized into three overarching themes: PbD-focused findings, leadership and organizational findings, and regulator-focused findings. The article argues that privacy continues to persist as an engineering problem despite PbD, that (related to that) there is growing recognition of privacy as an issue of organizational change and leadership, and consequently, that the role of the regulator must evolve if PbD is to become a meaningful regulatory tool, an evolution that carries with it both risks and opportunities for privacy.
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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.046 | 0.019 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".