National Broadband Strategies for Developed and Developing Countries: A Comparative Review and Lessons
Bibliographic record
Abstract
Today the Internet has become a fundamental part of our economic and social infrastructure. With some 2 billion users worldwide in 2010 [ITU, 2010a], it provides businesses, communities and individuals with a common global platform for communication and commerce. In parallel, the use of the increasingly intelligent wireless cell phone has exploded. It has become the most widely used communications device in the world, and the communications device of choice in developing countries. International Telecommunications Union estimates [ITU, 2010a] indicate that over 5 billion were in use by the end of 2010. “Smartphones” like the Apple iPhone and its competitors, and the RIM Blackberry are already in widespread use; “tablet computers” like the Apple iPad and its competitors are becoming increasingly popular. A recent Boston Consulting Group report forecasts that by 2016 mobile devices – smartphones, tablet computers, etc. – will account for four out of five broadband connections. Broadband is seen by many countries as a basic infrastructure which will facilitate economic growth, participation in the Internet economy and increased competitiveness. A ubiquitous and advanced broadband telecommunications infrastructure provides the essential platform for the efficient functioning of the Internet Economy, as railways, highways and the electricity grid do for an industrial economy. Broadband deployment is the great infrastructure challenge of the early 21st century, comparable to the building of earlier transformative networked infrastructures like railways in the 19th century, the electricity grid in the first half of the 20th century and the US Interstate highway system in the second half. Governments played an important role in the deployment of these earlier networked infrastructures, using statutory powers to clear rights of way, facilitating private sector investments through loan guarantees and guaranteed rates of return, and making direct investments where required. Rather than rely solely on market forces to guide the deployment of a national broadband infrastructure, many governments have moved to adopt more formal national mechanisms with a greater role for governments in planning and setting national goals and targets, usually through a National Broadband Plan or strategy. Over 20 countries have launched major national initiatives to accelerate broadband deployment, or are formulating such strategies [OECD, 2011]. These include developed countries like Australia, Korea, Singapore, Sweden, the USA and UK, as well as developing countries like Brazil and India. In this paper we shall examine a selected set of national broadband strategies, for both developed and developing countries, including goals, targets, funding models, the role of governments and implementation strategies. The purpose is to find out what worked, what did not, the problems encountered and lessons of general applicability, as well as lessons specific to developed and developing countries. In particular, we shall look at facilities based competition versus functional or structural separation combined with competition at the service level; issues related to universality and bridging the geographic digital divide; and issues related to the re-allocation of spectrum to meet the rising demand for advanced wireless broadband services and the use of spectrum revenues for funding broadband deployment initiatives. Policymakers in both developed and developing countries need to identify the socio-economic impacts of such broadband deployment initiatives. They also need to define the appropriate roles of governments, beyond the traditional regulatory and spectrum management roles, recognizing the need to tailor these roles to particular national circumstances. Further, there is a need to identify the optimal institutional mechanisms that can deliver broadband infrastructure and services. A dialogue between policymakers and researchers may also help to develop the outline of a medium term Policy Research Agenda, covering identified current and future issues which will require further work.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.023 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".