Local Nets on a Global Network: Filtering and the Internet Governance Problem
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
More than three dozen states around the world take part in censoring what their citizens can see and do on the Internet.This practice is increasingly widespread, with extensive filtering regimes in place in China, Iran, Burma (Myanmar), Syria, and Uzbekistan.Censorship using technological filters is often coupled with restrictive laws related to what the press can publish, opaque surveillance practices, and severe penalties for people who break the state's rules of using the Internet.This trend has been emerging since at least 2002.As Internet use overall and the practice of online censorship grow, heads of state and their representatives have been gathering to discuss the broad topic of "Internet governance" at a series of high-profile, global meetings.These meetings have taken the form of periodic World Summits on the Information Society and, more recently, meetings of the Internet Governance Forum.The widespread practice of blocking citizens from accessing certain information on the Internet from within a given state offers a point of engagement for the Internet governance debate that takes place at these summits and forums.Those who have participated in and lead these global efforts-the World Summit on Information Society's planners, the members of the United Nations ICT Task
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it