Privacy Advocacy from the Inside and the Outside: Implications for the Politics of Personal Data Protection in Networked Societies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract For the most part, privacy and data protection laws arose not through grassroots pressure but through interactions between governmental and business elites in the context of broader international harmonization efforts. Thus, civil society activists have rarely been seen as a client constituency with equivalent weight to governmental and business interests. There is evidence, however, that the privacy advocacy network is becoming more influential in comparative context. In most countries, a network of advocates has emerged with a relatively distinct profile from the “official” data protection authorities. Individual advocates play several conflicting roles and often exist within groups with wider civil liberties, human rights, digital rights, or consumer interests. Those at the center of the privacy advocacy network possess a set of core beliefs about the importance of privacy, and as one passes to the outer edges the issue becomes more and more peripheral. Privacy advocacy is beginning to occur from both the inside, and the outside, representing an important shift in the evolution of privacy protection policy both nationally and internationally, and producing difficult tensions between the two networks.
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.
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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it