A Map of Broadband Availability in Canada's Indigenous and Northern Communities: Access, Management Models, and Digital Divides (Circa 2009)
Bibliographic record
Abstract
In 2009, I participated in a project to map broadband availability ([> or =] 1.544 Mbps) in Canada's Indigenous and Northern communities, in collaboration with seven Regional Management Organizations (RMOs) partnered through Canada's First Nations SchoolNet (FNS) program. This article reports on the data collected to date, and provides an initial framing and exploration of that data in the context of Canada's national connectivity profile and several hypothesised access management models. I hypothesise that the management models, namely third-party commercial, Indigenous commercial, First Nations authority, and Indigenous social enterprise, shape broadband access in different ways, and also reflect different geographic conditions. I explore my hypotheses through a micro-census oriented methodology that reveals linkages between access management, geographic conditions, and digital divides among Canada's Indigenous and Northern regions.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".