Preface: Privacy Revisited: A Global Perspective on the Right to Be Left Alone
Bibliographic record
Abstract
Rapid technological change the advent of Big Data and the creation of societywide government surveillance programs have transformed the accessibility of highly personal information these developments have highlighted the ambiguous treatment of privacy and personal intimacy National legal systems vouchsafe and define "privacy" and its first cousin "dignity" in different ways that reflect local legal and cultural values Yet in an increasingly globalized world purely local protection of privacy interests may prove insufficient to safeguard effectively fundamental autonomy interests "“ interests that lie at the core of selfdefinition personal autonomy and freedom Privacy Revisited A Global Perspective on the Right to Be Left Alone Oxford University Press 2016 articulates the legal meanings of privacy and dignity through the lens of comparative law and argues that the concept of privacy requires a more systematic approach if it is to be useful in framing and protecting certain fundamental autonomy interests The book begins by providing relevant and reasonably detailed information about both the substantive and procedural protections of privacydignity in the US Canada South Africa the United Kingdom and among Council of Europe member states Second the book explores the inherent tension between affording significant legal protection to the right of privacy or human dignity and securing expressive freedoms notably including the freedom of speech and of the press Indeed careful consideration of the constitutional protection afforded privacy across different legal systems helps to illuminate some of the underlying social and political values that lead the US to fail to protect privacy as reliably or as comprehensively as other liberal democracies Finally the book establishes that although privacy and speech come into conflict with some regularity it is both useful and necessary to start thinking about the important ways in which both rights are integral to the maintenance of democratic selfgovernment In the era of Big Data we should consider carefully the important ways that privacy and speech are complementary rather than conflicting human rights values Simply put democratic selfgovernment presupposes an ongoing dialogue among citizens but an open dialogue about government simply cannot exist in a surveillance state
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.022 |
| Scholarly communication | 0.011 | 0.014 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.007 | 0.023 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".