Toward Universal Broadband in Rural Alaska
Bibliographic record
Abstract
The TERRA-Southwest project is extending broadband service to 65 communities in the Bristol Bay, Bethel and Yukon-Kuskokwim regions. A stimulus project funded by a combination of grants and loans from the Rural Utilities Service (RUS), TERRA-Southwest has installed a middle-mile network using optical fiber and terrestrial microwave. Last-mile service will be through fixed wireless or interconnection with local telephone networks. The State of Alaska, through its designee Connect Alaska, also received federal stimulus funding from the National Telecommunications and Information Administration (NTIA) for tasks that include support for an Alaska Broadband Task Force “to both formalize a strategic broadband plan for the state of Alaska and coordinate broadband activities across relevant agencies and organizations.” Thus, a study of the impact of the TERRA project in southwest Alaska is both relevant and timely. This first phase provides baseline data on current access to and use of ICTs and Internet connectivity in rural Alaska, and some insights about perceived benefits and potential barriers to adoption of broadband. It is also intended to provide guidance to the State Broadband Task Force in determining how the extension of broadband throughout the state could contribute to education, social services, and economic activities that would enhance Alaska’s future. Results of the research could also be used proactively to develop strategies to encourage broadband adoption, and to identify applications and support needed by users with limited ICT skills.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".