Public good, private providers?: Alternative internet networks in Alberta
Bibliographic record
Abstract
Despite high-speed broadband access being named a basic service by the Canadian Radio-television and Telecommunications Commission in late 2016, many Canadians remain cut off from the internet, unable to participate in the social, economic, and political facets of life that have increasingly moved online. This research project considers existing alternative internet network models in Alberta. Instead of waiting for incumbent internet service providers to solve the problem of universal access, several Albertan communities have taken steps to connect themselves. Twenty years after the inception of the provincial internet backbone, the SuperNet, how have Albertan communities engaged with internet infrastructure? As politicians, regulators, and citizens increasingly state the essential nature of high-quality, affordable internet service as a public good, what lessons, if any, can be learned from the different ways non-incumbent operators conceptualize, build, and operate alternative networks? Using qualitative interviews, policy documents, and marketing materials, I focus on three network models: a fixed wireless access network in a rural community, a non-profit internet exchange, and a municipally-owned and operated fibre network in an urban centre. Drawing upon political economy of communications literature as a theoretical framework, I consider what policy recommendations can be made based on these case studies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.013 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".