Bibliographic record
Abstract
Privacy rights are growing apace, as can be seen from a continuing stream of judgments from UK and European courts, the rise of special interest privacy groups and other institutions tasked to protect privacy. Privacy has – its proponents suggest – at last arrived as a fully fledged legal right. However, despite these advancements, I suggest that privacy is becoming less prevalent in society; primarily because of technological and cultural changes, but also because the technical legal implementation of privacy is highly problematic. In this article it is argued that this seeming paradox should be more critically examined by socio-legal researchers who, to date, have done little to test the assertions and assumptions of the privacy lobby. This article maintains that there is a need for more investigation of the basis and assumptions behind data protection and privacy law and that a more robust analysis of the claims and rhetoric for these rights will change our attitudes towards privacy developments. The sociological conception that ‘underlying all social interaction there seems to be a fundamental dialectic’ will be used to undermine the legal notion of privacy as an individualistic ‘fundamental right’.
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 | 0.014 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.013 | 0.082 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.009 | 0.010 |
| 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".