Broadband Adoption in Remote Regions: An Evaluation of Broadband Projects in Alaska Villages
Notice bibliographique
Résumé
Alaska is the largest state in the U.S. but with the nation’s lowest population density, of only 1.2 persons per square mile. Its total population now exceeds 710,000, of which 14.8 percent are Alaska Natives. Approximately two-thirds of the indigenous population lives in more than 200 rural villages, most of which are remote settlements with fewer than 200 people. Several recent studies have examined broadband adoption and reasons cited for nonadoption among U.S. residents, with some data disaggregated by various demographic and ethnic criteria (age, education level, urban/rural, gender, ethnicity, etc.) Studies by the FCC and NTIA cite key reasons for non-adoption of broadband as price and perceived relevance. While helpful in increasing our understanding of barriers to adoption among various groups including minorities, these studies do not have samples of Alaska Natives large enough to provide any valid findings, and samples for Alaska as a whole are too small to provide reliable data on rural ICT access and use. Also, the metrics used in these studies may not be relevant for small indigenous communities where access may primarily be at schools, libraries (where they exist), community centers, or tribal/local government offices. Two major stimulus-funded projects in rural Alaska provide an opportunity to do gather reliable data on rural broadband adoption and use, and perceived barriers to adoption. TERRA Southwest, an RUS-BIP funded project, is extending broadband facilities to 65 predominantly Native Yupik communities in Bristol Bay and the Yukon-Kuskokwim regions. Also, an NTIA BTOP project called OWL (Online with Libraries) will upgrade connectivity in 100 libraries, most of which are in remote communities. Concerning policy, the FCC has issued several notices to solicit information on broadband needs in tribal regions, including Alaska. Thus, research on adoption of broadband in indigenous Alaska communities is highly relevant and timely. This paper will propose an analytical framework for broadband adoption that takes into consideration the geographical and cultural environments in indigenous communities of rural Alaska. It will also report on preliminary results of evaluations of the TERRA and OWL projects by the Institute of Social and Economic Research (ISER) at the University of Alaska Anchorage. The first phase of the TERRA evaluation will include a telephone survey of 400 residents of the region to gain information on current ownership and use of ICTs including computers and smartphones, and use of Internet connections at home, work, and/or at schools, libraries, and tribal offices. It will also include questions about interest in higher speed connectivity, possible applications, and perceived barriers to use. Interviews will also be conducted with representatives of Native corporations and tribal organizations, economic development organizations, local businesses, and major sources of income such as fisheries, social services, and tourism. The OWL evaluation will provide data about current use of libraries for Internet access and demand for community access to broadband for applications such as distance education, e-goverment services, and entrepreneurship. While Alaska may represent an unusual case because of its geography and small remote communities, a similar adoption framework could be applied in other regions with significant indigenous populations such as tribal lands and the intermountain West. Further, the framework may be relevant for considering how this approach to adoption could be applied in other multicultural contexts and in developing regions.
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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 | 0,010 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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 ».