Bibliographic record
Abstract
This chapter is critically commenting on the augmenting policy of public surveillance through the ‘Public Camera Surveillance’ system (CCTV technology) in Greece and in other countries such as the UK, USA, Canada, and Australia. It presents the arguments in favor and against such policies and the main threats that such policy-making poses for the freedom of the individual as represented in the relevant jurisprudence of the ECtHR. The main argument of the presentation underlines the need for the interpretive deduction of a right to anonymity or otherwise of a right to public privacy from the traditional notion of privacy. This right enables the individual to enjoy his/her privacy in public, thus allowing him/her to circulate in public assured that his/her presence will remain anonymous and permitting him/her to merge within the rest of the crowd. Such a right is specifically valuable in order to protect the political autonomy of the individual as a participant of demonstrations and public movements or manifestations under the precondition that his/her deeds do not merit the state’s intervention. The presentation closes with some remarks on the changing social and political ethos that brings forward the demand of public surveillance as a need for public safety.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| 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".