Bibliographic record
Abstract
In every advanced industrial society, there exist disparate groups who have tried to spotlight excessive levels of surveillance, online and offline. They have protested ID cards, video-surveillance programs, intrusive marketing practices on the Internet, the integration of personal databases, and so on. They have attempted to “out” excessively intrusive organizations, and to render transparent their surveillance practices. There is plenty of evidence that these groups have become more active and more visible. But who are the “privacy advocates”? What are their main strategies, and why have their activities assumed a greater importance? The range of issues surrounding the collection, use, processing and dissemination of personal information by public and private organizations employing the most sophisticated information technologies is commonly assumed to be one of the critical issues of the “digital age.” But how do the advocates attempt to translate a strong, but vague sense, of public unease about privacy into meaningful social action? Is there the potential for a more coherent and international social movement to coalesce around these issues of similar strength and visibility to the environmental movement? \n \n \nDr. Colin Bennett received his Bachelor’s and Master’s degrees from the University of Wales, and his Ph.D from the University of Illinois at Urbana-Champaign. Since 1986 he has taught in the Department of Political Science at the University of Victoria, where he is now Professor. From 1999-2000, he was a fellow at the Kennedy School of Government Harvard University. His research has focused on the comparative analysis of information privacy protection policies at the domestic and international levels. In addition to numerous articles, he has published three books: Regulating Privacy: Data Protection and Public Policy in Europe and the United States (Cornell University Press, 1992); Visions of Privacy: Policy Choices for the Digital Age (University of Toronto Press, 1999, with Rebecca Grant);The Governance of Privacy: Policy Instruments in the Digital Age (Ashgate Press, 2003, with Charles Raab).
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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 | 0.002 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 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".