Global platform governance and the internet-governance impossibility theorem
Bibliographic record
Abstract
Economist Dani Rodrik argues that global economic governance is characterized by a trilemma: ‘we cannot have hyperglobalization, democracy, and national self-determination all at once. We can have at most two out of three’. This trilemma can also be applied to internet governance and global platform governance as a corollary global internet-governance impossibility theorem . This trilemma, which emphasizes who sets the rules and the degree of democratic accountability they face, offers us a way to evaluate online content-regulation proposals. This article applies this framework to four prominent platform-governance proposals: Facebook’s proposal for a global ‘Oversight Board’; David Kaye’s book Speech Police ; the United Kingdom’s Online Harms White Paper ; and French president Emmanuel Macron’s speech to the 2018 Internet Governance Forum. Of the four, only Macron’s framework offers a pathway to reconciling democratic accountability with the existence of different legitimate views on how content should be regulated.
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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 | 0.013 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.025 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".