Bibliographic record
Abstract
For almost a decade, executives, scholars, and trade diplomats have argued that filtering, censorship, localization requirements and domestic regulations are distorting the cross-border information flows that underpin the internet. Herein I make 5 points about digital protectionism. 1. Digital protectionism differs from protectionism of goods and other services because trade in information is different from trade in goods and other services. Information is intangible, highly tradable, and some information is a public good which governments must provide and regulate effectively. 2. It will not be easy to set international rules to limit digital protectionism without a shared set of norms and definitions. However, we can only obtain greater clarity with trade disputes and clearer trade rules. 3. The US, EU, and Canada have labeled other countries policies’ protectionist, yet their arguments and actions sometimes appear hypocritical. 4. China allegedly has used a wide range of cyber-strategies including distributed denial of service (DDoS) attacks (bombarding a web site with service requests) to censor information flows and impede online market access beyond its borders. WTO members have yet to discuss this issue and the threat it poses to trade norms and rules. 5. Digital protectionism may be self-defeating. Governments that adopt digital protectionist strategies could experience unanticipated side effects, including reduced access to information, internet stability, and generativity. Digital protectionism may also undermine human rights and scientific progress. Recommendations — Policymakers Should: 1. Ask the WTO Secretariat to examine whether domestic policies that restrict information (short of exceptions for national security, privacy, and public morals) constitute barriers to cross-border information flows that could be challenged in a trade dispute. 2. Convene a study group at the WTO to examine the trade implications of governmental use of malware or DDoS attacks to improve the competitiveness of their firms or censor the internet in other countries. These tactics should be banned, although the WTO may not be the best forum for discussion of these problems. 3. During each WTO member state’s trade policy review process, the members of the WTO should monitor how each member’s rules governing information flows potentially distort trade. 4. Propose and negotiate an international agreement that defines and limits digital protectionism and delineates clear and limited exceptions.
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 | 0.002 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".