Bibliographic record
Abstract
Abstract The protection of privacy has been on the policy agenda since Alan Westin first published his seminal work, Privacy and Freedom, in 1967. The book was followed swiftly by a series of governmental studies in France, the United Kingdom, Canada, Sweden, and the United States, and each of these countries subsequently passed data protection laws based on Westin’s definition of privacy as informational control. By 2000, over forty countries around the world had passed similar legislation as part of an ongoing international effort to harmonize the legal regime governing privacy. However, critics argue that the legislative activity of the past forty years has done little to constrain the collection of massive amounts of personal information on the part of governments and corporations. Sociologists have been particularly critical of Westin’s conceptualization of privacy, arguing that as “appealing and seemingly intuitive as this concept is, it plainly doesn’t work.” Their argument is supported by the fact that data protection has been unable to stop the rollout of technologies like closed-circuit television cameras in public places, remote-activated location devices in cell phones, iris scans in school cafeteria lunch lines, and security cameras in bathrooms, hotel rooms, and school buses, in spite of concerns that the surveillance these technologies enable may have deleterious effects on our social and political relationships. The conceptualization of privacy as informational control has also arguably displaced broader—and potentially more empowering—discourses rooted in a human rights model that seeks to protect human dignity and democratic freedoms in the surveillance society.
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 | 0.021 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.099 |
| Scholarly communication | 0.018 | 0.020 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".