The First Mile of Broadband Connectivity in Communities: Introduction to the Special Issue
Bibliographic record
Abstract
In this special issue , “First Mile” refers to broadband infrastructure development that puts the needs of local communities first and ahead of the needs of private sector telecommunication corporations. This approach is one that prioritizes community-led solutions that seek to create local economic and social opportunities and to minimize the digital divide between rural and urban users (see: McMahon, O’Donnell, Smith, Walmark, Beaton, & Simmons, 2011). Around the world, broadband infrastructure and networks are rapidly being developed in communities marginalized in the network society. The relationships, structures and agreements put into place at this early development stage will shape how broadband systems are created and managed in the future. First Mile strategies include developing locally owned and managed telecommunication structures and networks. This special issue profiles First Mile projects and efforts that are as innovative, unique and vibrant as the communities from which they emerge. Further, this issue highlights some of the challenges facing First Mile initiatives. Several contributions in this issue deal with Canadian cases and others with remote and rural contexts around the world.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".