Facebook and the Cambridge Analytica Scandal: Privacy and Personal Data Protections in Canada
Bibliographic record
Abstract
In 2018, the Cambridge Analytica/Facebook scandal made front page news, a data breach that allowed a third-party -Cambridge Analytica -access to the personal data of millions in several countries, including over 600,000 Canadians. The scandal brought to light privacy issues to regulator and in the aftermath, Canada conducted an investigation into this unsanctioned use of data. This thesis explores the details of that scandal and the resulting Canadian investigation by the Standing Committee on Access to Information, Privacy and Ethics (ETHI) and the Office of the Privacy Commissioner (OPC), as well as drawing on information from the 2009 Canadian Internet Policy and Public Interest Clinic (CIPPIC) complaint with the OPC, and the Broadcasting and Telecommunications Legislative Review (BTLR). These public records are used to provide a lens through which to explore topics of privacy and personal data protection in Canada and what they might mean in a social media platform context. This thesis explores the different regulatory mechanisms and makes some recommendations to improve personal data protection and privacy regulations in Canada, including behavioral and structural regulatory solutions that might mitigate similar such scandals in the future.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".