Avoiding 'Dog in the Manger' Regulations - A Nuanced Approach to Net Neutrality in Canada
Bibliographic record
Abstract
This paper argues that most forms of proposals seek a regulatory guarantee in an already competitive market, but there is no clear evidence that the prescriptive rules that they propose yield significant benefit over and beyond what market forces produce in both the access and the content and applications sides of the Internet market. The paper argues that Canada's Telecommunications Act, in particular Sections 27 and 36 and the case-by-case approach taken by the Canadian Radio-television and Telecommunications Commission (CRTC) in their application, provides a sound framework to address concerns without any need for new prescriptive ex ante rules. Based on Canada's commitment to minimal interference in the telecommunications sector, it is argued that the standard for evaluating ISPs' behaviour under Sections 27 and 36 is whether such behaviour will substantially impede competition in the content and applications market. The paper argues that most forms of proposals will fail this competitive outcome test. In order to remain relevant as a public policy ideal in an already competitive environment, net neutrality should be redefined more narrowly outside its overly broad regulatory guarantee box to complement, not undermine, market forces. Such a complementary role can be found potentially in cases where there is information failure or asymmetry with respect to ISP network management practices vis-a-vis consumers. Viewing as net- work management transparency complements the competitive outcome framework of the Policy Direction and sections 27 and 36 of the Telecommunications Act in that the more transparent a network management practice is to downstream access consumers, the less likely it is to have significant negative effect on competition upstream in the Internet content and applications market.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.021 |
| Scholarly communication | 0.017 | 0.004 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".