Economic Regulation of Voice over IP Services: A Cross-Jurisdictional Survey
Bibliographic record
Abstract
As incumbent telcos introduce IP technology into their networks, a question arises about whether the new wave of voice services which this technology enables (VoIP) should be regulated on the same restrictive basis as the incumbents' conventional circuit-switched services. NRAs in several jurisdictions have recently addressed this issue. In this paper, the author examines the policies adopted by the NRAs in eleven of these jurisdictions: France, the UK, Ireland, Germany, the Netherlands, Italy, Spain, Denmark, Sweden, the US and Canada. The author finds that, with one exception, NRAs that have determined that VoIP is in whole or in part in the same market as retail PSTN calls have also decided that the nature of the regulatory obligations imposed on the two types of service should nevertheless differ. The exception is Canada. The author also finds that this near-consensus is achieved despite a difference of views on the issue of appropriate market definition. For example:• Six jurisdictions have found that VoB is part of the same market as narrowband retail calls, while three others have decided the opposite.• Three jurisdictions draw a distinction between Voice over Broadband (VoB) and Voice over Internet (VoI) (unmanaged VOB) for regulatory purposes, while four others, while adverting to the distinction, regard it as irrelevant for regulatory purposes.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".