Bibliographic record
Abstract
Preface, Aaron Doyle, Randy Lippert and David Lyon 1. Introduction, Aaron Doyle, Randy Lippert and David Lyon Part 1: Situating Camera Surveillance Growth 2. 'There's no Success like Failure and Failure's no Success at all': Some Critical Reflections on the Global Growth of Camera Surveillance, Clive Norris 3. What Goes Up, Must Come Down: On the Moribundity of Camera Networks in the UK, Gavin Smith 4. Seeing Surveillantly: Surveillance as Social Practice, Jonathan Finn Part 2: International Growth of Camera Surveillance 5. Cameras in Context: A Comparison of the Place of Video Surveillance in Japan and Brazil, David Murakami Wood 6. The Growth and Further Proliferation of Camera Surveillance in South Africa, Anthony Minaar 7. The Piecemeal Development of Camera Surveillance in Canada, Emily Smith Part 3: Evolving Forms and Uses of Camera Surveillance 8. The Electronic Eye of the Police: The Provincial Information and Security System in Istanbul, Alanur Cavlin Bozbeyoglu 9. Policing in the Age of Information: Automated Number Place Recognition, Patrick Derby 10. Video Surveillance in Vancouver: Legacies of the Games, Micheal Vonn and Philip Boyle 11. Selling Surveillance: The Introduction of Cameras in Ottawa Taxis, Aaron Doyle and Kevin Walby 12. Deploying Camera Surveillance Images: The Case of Crime Stoppers, Randy Lippert and Blair Wilkinson 13. Hidden Changes: From CCTV to 'Smart' Video Surveillance, Joseph Ferenbok and Andrew Clement Part 4: Public Support, Media Visions and the Politics of Representation 14. Anti-surveillance Activists v. The Dancing Heads of Terrorism: Signal Crimes, Media Frames, Symbolic Politics and Camera Promotion, Laura Huey 15. Surveillance Cameras and Synopticism: A Case Study in Mexico City, Nelson Arteaga Botello 16. Surveillance Culture and Appropriation: CCTV as Found in Footage in Manu Luksch's Faceless, Martin Zeilinger 17. 'What Do You Think?': International Public Opinion of Camera Surveillance, Danielle Dawson 18. Towards a Framework of Contextual Integrity: Legality, trust and compliance of CCTV Signage, Mark Lizar and Gary Potter 19. Mitigating Asymmetric Visibilities: Towards a signage code for surveillance camera networks, Andrew Clement and Joseph Ferenbok 20. Is it a 'Search'?: The Legal Context of Camera Surveillance in Canada, Mathew Johnson 21. Privacy As Security: Surveillance Camera Signage and Informed Consent, Christopher Burt 22. Reversing the Conventional Wisdom on Video Surveillance in Canada, Robert Ellis Smith
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.641 | 0.531 |
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".