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Access Denied

2008· book· en· W4232208315 on OpenAlexaboutno aff

Bibliographic record

VenueThe MIT Press eBooks · 2008
Typebook
Languageen
FieldSocial Sciences
TopicFreedom of Expression and Defamation
Canadian institutionsnot available
Fundersnot available
KeywordsThe InternetPoliticsPolitical scienceInternet accessFilter (signal processing)DozenPublic relationsSociologyLawMedia studiesComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

A study of Internet blocking and filtering around the world: analyses by leading researchers and survey results that document filtering practices in dozens of countries. Many countries around the world block or filter Internet content, denying access to information that they deem too sensitive for ordinary citizens—most often about politics, but sometimes relating to sexuality, culture, or religion. Access Denied documents and analyzes Internet filtering practices in more than three dozen countries, offering the first rigorously conducted study of an accelerating trend. Internet filtering takes place in more than three dozen states worldwide, including many countries in Asia, the Middle East, and North Africa. Related Internet content-control mechanisms are also in place in Canada, the United States and a cluster of countries in Europe. Drawing on a just-completed survey of global Internet filtering undertaken by the OpenNet Initiative (a collaboration of the Berkman Center for Internet and Society at Harvard Law School, the Citizen Lab at the University of Toronto, the Oxford Internet Institute at Oxford University, and the University of Cambridge) and relying on work by regional experts and an extensive network of researchers, Access Denied examines the political, legal, social, and cultural contexts of Internet filtering in these states from a variety of perspectives. Chapters discuss the mechanisms and politics of Internet filtering, the strengths and limitations of the technology that powers it, the relevance of international law, ethical considerations for corporations that supply states with the tools for blocking and filtering, and the implications of Internet filtering for activist communities that increasingly rely on Internet technologies for communicating their missions. Reports on Internet content regulation in forty different countries follow, with each two-page country profile outlining the types of content blocked by category and documenting key findings. Contributors Ross Anderson, Malcolm Birdling, Ronald Deibert, Robert Faris, Vesselina Haralampieva [as per Rob Faris], Steven Murdoch, Helmi Noman, John Palfrey, Rafal Rohozinski, Mary Rundle, Nart Villeneuve, Stephanie Wang, Jonathan Zittrain

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.098
Threshold uncertainty score0.328

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.035
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0050.005
Scholarly communication0.0120.016
Open science0.0010.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0980.015

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.

Opus teacher head0.109
GPT teacher head0.344
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations229
Published2008
Admission routes1
Has abstractyes

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