Nordicity and its relevance for northern Canadian infrastructure development
Bibliographic record
Abstract
Infrastructure development in Canada’s northern regions remains a challenge. Although scholars and policy-makers recognize the significant socio-economic potential of northern infrastructure, the prevailing piecemeal approach does not respond to many of the challenges faced by Indigenous communities. A pan-Canadian approach, such as a Northern Corridor, can circumvent some of the disadvantages stemming from fractured and uncoordinated initiatives but it still underlies the diverse environmental and socio-economic conditions across the Canadian North. The Nordicity index, originally developed by Hamelin, reflects northern Canada’s diversity and has been applied as a public policy tool, e.g. for determining northern living allowances or adapted for transportation development. However, these indices are spatio-temporally fixed which means they do not recognize changing spatial patterns of northern mobility. Thus, this paper argues that northern infrastructure development should be informed by Indigenous spatial practices of mobility. To this aim, the paper investigates the role of Nordicity in Canadian policy-making and analyses how northern Indigenous spatial practices of mobility have transformed throughout the last century. The Nordicity index recognizes the environmental and socio-economic conditions across Canada’s diverse northern regions but it should be complemented with an analysis of the spatial practices of northern Indigenous Peoples to inform future infrastructure development.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| 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".