Bibliographic record
Abstract
This paper explores the role of counties in the deployment of high-speed internet (“broadband”) networks in the United States. Counties play crucial roles in local governance, but have been absent from discussions of broadband policy, planning and deployment by both lawmakers and scholars. Rectifying this, this paper reports the results of a survey of counties in the Commonwealth of Virginia. Using thematic coding analysis, themes from our survey include (1) mapping and the ongoing issue of identifying un- and under-connected areas; (2) funding and the use of public money; (3) strategic partnerships with electric cooperatives, investor-owned ISPs, and other counties and (4) urban bias. Based on these themes, we argue that countries play three crucial, but heretofore neglected, roles in broadband deployment: funder, partner, and mobilizer. Moreover, we argue that counties are eager for greater responsibility and authority over deployment. This paper concludes with recommendations for how Virginia can amplify the roles and responsibilities of counties in broadband deployment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".