Interrogating Privacy in the digital society: media narratives after 2 cases
Bibliographic record
Abstract
The introduction of information technology (IT) in the society and its pervasiveness in every aspect of citizens’ daily life highlight societal stakes related to the goals regarding the uses IT, such as social networks. This paper examines two cases that lack a straightforward link with privacy as addressed and protected by existing law in Europe (EU) and the United-States (USA), but whose characteristics, we believe fall on other privacy function and properties. In Western societies, individuals rely on normative discourses, such as the legal one, in order to ensure protection. Hence, the paper argues that other functions of privacy need either further framing into legislation or they need to constitute in themselves normative commitments of an ethical nature for technology development and use. Some initiatives at the EU level recall such commitments, namely by developing a normative discourse based on ethics and human values. We argue that we need to interrogate society about those normative discourses because the values we once cherished in a non-digital society are seriously being questioned.
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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 | 0.018 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.027 | 0.038 |
| Scholarly communication | 0.022 | 0.029 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.012 | 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".