Mobile Communications Policies and National Broadband Strategies in Developed and Developing Countries: Lessons, Policy Issues and Research Challenges
Notice bibliographique
Résumé
The intelligent mobile phone has become the most widely used communications device in the world and the access device of choice in the developing world. The International Telecommunications Union’s report “The World in 2015: ICT Facts and Figures” estimates that there were some 7.1 billion mobile service subscriptions by the end of 2015, corresponding to a global population of some 7.4 billion. Mobile cellular penetration rates stand at 97% globally, 121% in developed and 92% in developing countries. Mobile broadband is the most dynamic market segment. There are now three times as many mobile broadband subscriptions as fixed ones.Spectrum is the lifeblood of mobile communications services. As high-speed mobile Internet access becomes more readily available and affordable, mobile devices are being used widely for a variety of bandwidth-hungry applications. Therefore the demand for additional spectrum bandwidth is likely to increase rapidly and outstrip the supply for the next few years. Issues related to spectrum allocation and management have become an important component of any national wireless broadband strategy.Mobile Internet access and use is becoming the new norm. Policy makers in developing countries, in addition to dealing with the conventional issues related to facilitating the growth of mobile communications (e.g. spectrum availability and re-allocation, infrastructure sharing and interconnection, service pricing and availability), will need to formulate policies, and regulations where required, to address the new challenges related to the large scale migration of mobile users from 2G to 3G/4G broadband communications networks. Many governments have instituted a range of supply side policies to accelerate broadband deployment, increase availability and reduce costs. However, the most effective design of complementary demand side policies remains uncertain. This international panel will focus on the impact of the widespread penetration and use of intelligent mobile devices, in both developing and developed countries. The panel will discuss issues such as:• What role does mobile broadband play in different national broadband strategies, and how is it integrated with the wireline component?• Other than efficiently allocating and managing the use of the spectrum, what other roles can governments and regulators play in enabling the continued growth of mobile telecommunications services? • Last but not least, what conceptual frameworks do researchers and policy-makers use when shaping communications policy? What is the role of evidence in shaping current approaches? The Panelists, whose expertise covers various countries and regions, will discuss and compare strategies being used in developed countries like the US, Australia and the EU, and developing countries like Mexico, Brazil and India, among others. We wish to find out what has worked, what did not, the problems encountered and whether there are lessons to be learned that are of general applicability, as well as for particular countries. We wish to explore the possibilities and limitations of learning from other nations’ and regions’ experiences, identifying common policy challenges and medium term research requirements of interest to the TPRC community.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,006 |
| Études des sciences et des technologies | 0,002 | 0,006 |
| Communication savante | 0,012 | 0,015 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,005 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».