A Desiderata for Wireless Broadband Networks in the Public Interest
Bibliographic record
Abstract
There is currently an expanding range of initiatives in North America, and world-wide, attempting in various ways to develop public internet infrastructures. Discussion about them so far has concentrated on the benefits they espouse (bridge the digital divide, promote commerce,..), what technological configuration is best (e.g. WiFi, fiber, hybrids of these,..) and who should own (and perhaps build) them (e.g. private sector, public sector, or a partnership of these,...). What has been relatively absent to date is systematic analysis of the functional and performance characteristics of the infrastructure itself. Such an analysis would be invaluable in assessing the competing claims about such benefits, technologies and ownership models. This paper offers an analytic framework for assessing public internet infrastructures. Drawing initially on familiar criteria for communications infrastructures (e.g. ‘public interest, convenience and necessity’ from longstanding US public utility law, ‘universal and affordable’ from telecommunications legislation in the US, Canada, and elsewhere), it refines and expands these in light of contemporary internet initiatives. It thus presents a list of for public broadband infrastructure – a checklist of principles for building and operating them in the public interest. We examine each of these infrastructural characteristics in turn, describing what is meant by the term, and how it has been used in policy development as well as the relevant scholarly literature. These desiderata are illustrated using case studies of community/municipal wireless initiatives in North America. The paper also discusses how the desiderata can be used as a tool for assessing proposed and operational broadband networks.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.044 |
| Scholarly communication | 0.021 | 0.024 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.012 | 0.013 |
| Insufficient payload (model declined to judge) | 0.005 | 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".