Bibliographic record
Abstract
This paper qualitatively analyzes the suitability of different broadband access platforms to provide intermodal competition for the services provided today by the incumbent telephone operators, cable operators, and satellite operators with a particular focus on the provision of high speed internet access. As a baseline, the paper also presents the quantitative incremental economics for cable companies and telephone companies to provide high speed Internet access as a baseline. This paper is based on the analysis done by FCC Technology Advisory Council’s Broadband Access Working Group, which the author chaired as well as updated economics derived from the JP Morgan McKinsey Broadband 2001 report. The approach is to define the services that compete for the consumer’s dollar, examine the key economic factors that drive deployment economics, and then analyze the suitability of different platforms to deliver the services. Nine different new technology platforms that are capable now, or will be capable in the near future, of delivering most of the services considered are compared with the baseline of today’s cable and telephony. The suitability of delivering these services over the new platforms is a function of technical feasibility, state of development and deployment, and ability to compete with the economics of the existing alternatives. The conclusion is that any new technology platform will be quite challenged in most markets to compete with the cable operators and incumbent telephone companies for the delivery of high-speed Internet access either on a stand-alone basis or in conjunction with other services. Among the alternative technologies to cable and DSL, terrestrial wireless using either licensed spectrum below 5 GHz or unlicensed spectrum represents the best possibility. Even service providers using these technologies will be challenged to compete broadly for high speed Internet access. Customer acquisition and service and other non-technology costs are considerably greater than the technology costs. Therefore scale and the ability to offer new services on an incremental basis to existing services confer a distinct advantage to incumbents.
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 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 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".