Bibliographic record
Abstract
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.ContributorsRoss 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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 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; both teacher heads agree on what is shown here.
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".