Bibliographic record
Abstract
It has recently become fashionable within the surveillance studies community to subject the concept and regime of “privacy protection” to some very rigorous criticism. “Privacy” and all that it entails is argued to be too narrow, too based on liberal assumptions of subjectivity, too implicated in rights-based theory and discourse, insufficiently sensitive to the social sorting and discriminatory aspects of surveillance, and overly embroiled in spatial metaphors about “invasion” and “intrusion.” As a concept, and as a way to frame the various social and political challenges encountered within “surveillance societies,” it is inadequate. These critiques are important, and to some extent, have set scholarly inquiry on a new, exciting and broader, trajectory than that offered by privacy scholars. On closer examination, however, these critiques are often based on some faulty assumptions about the contemporary framing of the privacy issue, and about the governance of the issue. Privacy, as a concept, regime, a set of policy instruments, and as a way to frame civil society activism, shows an extraordinary resilience. Surveillance scholars must learn to live with it.
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 | 0.024 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.112 |
| Scholarly communication | 0.021 | 0.031 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.015 | 0.017 |
| Insufficient payload (model declined to judge) | 0.004 | 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".