Inadequate: The APEC Privacy Framework & Article 25 of the European Data Protection Directive
Bibliographic record
Abstract
The EU and APEC approaches represent two different ways of thinking about the purpose of privacy rights in personal information (a.k.a. “informational privacy” or “data privacy”). The European approach sees integrity and control over information about oneself as inherent to human dignity; informational privacy is treated as a fundamental right subject only to limited restrictions. In contrast, the approach evinced by APEC is a market-oriented cost/benefit calculus; control over personal information is seen as a beneficial policy goal when it can increase consumer confi- dence and promote economic growth — the implication being that it can also more easily give way in the face of competing economic arguments. These two approaches — one grounded in the language of rights, the other in the language of markets — result in significant differences in both the substantive and procedural protections each regime creates. This article argues that the two approaches are incompatible, and the tension this creates is revealed in the rules regarding the transfer of personal data from Europe to third countries.
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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.026 | 0.010 |
| Insufficient payload (model declined to judge) | 0.019 | 0.011 |
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".