Regulatory Lessons for Internet Traffic Management from Japan, the European Union, and the United States: Toward Equity, Neutrality and Transparency
Bibliographic record
Abstract
As network neutrality has been one of the most contentious Internet public policy issues of the past decade, this article provides a comparative overview of events, policies, and legislation surrounding Internet traffic management practises (ITMPs) (e.g., network neutrality) in Japan, the European Union, the United States, and Canada. Using the frame provided by Richard Rose of “hybrid lessons”to create a policy synthesis, the paper details the telecom policy environment, Internet Service provider competition, legislative jurisdiction, remedies for ITMPs, consumer transparency, and adherence to privacy protection in each country. The analysis focuses on Canada’s first significant regulatory effort to address network neutrality, which came during the Canadian Radio-television and Telecommunications Commission 2009 process on Internet traffic management. This paper presents a brief overview of the Canadian regulatory environment and the specific questions which were the subject of the CRTC review. Employing Richard Rose’s methods for comparative public policy analysis, we offer a number of regulatory “lessons” from Japan, the European Union, and the United States based on their experiences with traffic management issues. Applying these lessons to the Canadian context, we make several specific policy recommendations, among them that competition be encouraged within the Internet service provider space, that network management practises be reasonable and limited, and that ISPs provide full disclosure of network management policies and practises.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".