Reducing the Digital Divide in Rural Manitoba: A Proposed Framework
Bibliographic record
Abstract
Outside of larger centres across Canada public policies and corporate investments have left 2 million rural households under-served with broadband network capacity. After nearly 20 years of activities this gap may be closing, yet front line strategists suggest our rural digital divide will persist for years to come. A supplemental to the current approach is needed to connect these rural areas, yet it may require different technologies and social capital investment. This paper brings the reader inside a Manitoba working group (Forum) to reveal how applied research, assisted in formulating an integrated action framework that proposes an approach to provide access to users and expand the uses of broadband while calling for leadership and utilizing social marketing. New partnerships are envisioned across three levels of public sector, ISPs, and local businesses, along with youth and citizens. A proposed implementation framework is offered as an approach to incrementally provide specific rural broadband services to one area before moving to the next. This framework is not a silver bullet for all rural areas, but rather offers an approach that might be a useful starting point for under-served rural areas in Canada. Keywords: Rural broadband, under-served communities, access, availability, partnerships, integrated approach, implementation
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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 | 0.010 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.012 | 0.016 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".