Mobile Communications and National Broadband Strategies: Perspectives, Issues, Challenges and Lessons (Panel)
Notice bibliographique
Résumé
“Every day we are moving closer to having almost as many mobile subscriptions as people on earth…The mobile revolution is m-powering people in developing countries by delivering ICT applications in education, health, government, banking, environment and business. Let us all celebrate this mobile miracle…” Brahima Sanou, Director, ITU Telecommunications Bureau, “The World in 2013: ICT Facts and Figures.” The use of the increasingly intelligent mobile phone has exploded over the last decade. It has become the most widely used communications device in the world, and the access device of choice in the developing world. The ITU estimates that there were some 6.8 billion mobile service subscriptions by the end of 2013, corresponding to a global population of 7.1 billion. Mobile penetration rates stand at 96% globally, 128% in developed and 89% in developing countries. ITU estimates indicate that mobile broadband subscriptions increased from 268 million in 2007 to 2.1 billion in 2013, an average annual growth rate of 40%. There are now more than twice as many mobile broadband subscriptions as fixed ones. Spectrum is the lifeblood of wireless mobile communications services. As high-speed mobile Internet access becomes more readily available and affordable, the cell phone and other more intelligent mobile devices with greater functionalities (e.g. smartphones, tablet computers, laptops) are widely being used for bandwidth-hungry business applications as well as for personal and social purposes. Therefore the demand for additional spectrum bandwidth is likely to increase rapidly and outstrip its supply for the next few years. Ubiquitous wireline and wireless broadband infrastructure deployment is the great infrastructure challenge of the early 21st century. Mobile broadband communications requires an integration of wireless and wireline networks. Governments have a key role to play in efficiently allocating and managing the use of the spectrum and meeting the demand for additional spectrum bandwidth. Issues and challenges related to the efficient allocation and management of the spectrum will therefore become an important component of any national broadband strategy. This international panel will focus on the impact of the widespread penetration and use of the cell phone and other more intelligent mobile devices, in both developing and developed countries. It will examine and compare the role that wireless access and mobile broadband play in various national and regional broadband strategies; and how mobile communications is integrated with the wireline component of such strategies. The panelists will discuss strategies being used in the US, Australia, the EU, Mexico 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. An overall lesson seems to be “One size does not fit all”. This is a topic of continuing interest to the TPRC community. We wish to explore the possibilities and limitations of learning from other nations’ and regions’ experiences. A dialogue between the policymakers and researchers could help to identify current and future policy issues which will require further research work. Possible Panelists: Dr. Robert D. Atkinson, President, The Information Technology & Innovation Foundation (ITIF), Washington Prof. Rekha Jain, Professor, Indian Institute of Management, Ahmedabad (IIMA) and Executive Chair of the IIMA-IDEA Telecom Centre of Excellence (IITCOE) Prof. Judith Mariscal, Professor, Centro de Investigacion y Docencia Economica (CIDE), Director of the Telecommunications Research Program Telecom-CIDE, and member of the Steering Committee of DIRSI Prof. Catherine Middleton, Professor, Ted Rogers School of Information Technology Management, Ryerson University, Toronto Dr. Jean-Paul Simon, Director, JPS Public Policy Consulting and member EuroCPR Board
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 | 0,004 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,004 | 0,003 |
| Communication savante | 0,012 | 0,016 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,017 | 0,012 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,028 | 0,007 |
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 ».