Opportunities and Challenges for First-mile Development in Rural Hawaiian Communities
Bibliographic record
Abstract
The islands of Hawaiʻi are the most geographically remote locations on earth and connect to the global Internet via expensive submarine fiber. While citizens in densely populated areas such as Honolulu have several options for broadband coverage, there are gaps throughout the state. Many of those living in rural areas, including indigenous Hawaiian communities, suffer from a lack of critical infrastructures. For indigenous Hawaiians trying to gain equal access to educational and economic opportunities, health care, and linguistic and cultural preservation, this disparity is particularly troubling. We describe challenges faced by Native Hawaiian communities in developing affordable, high-quality broadband access and describe initiatives, to date, that seek to address them. We suspect that the conventional planning approach to broadband development is incongruent to the unique economic, social and cultural contexts present in Hawaiian rural communities. Our investigation explores the potential for community-initiated broadband projects that will enable indigenous Hawaiians more self-determination in the planning and management of broadband networks and services.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".