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Record W2731064947 · doi:10.22584/nr45.2017.003

Exploring Innovation in Northern Canada with Insights from the Mining Innovation System in Greater Sudbury, Ontario

2017· article· en· W2731064947 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Northern Review · 2017
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSituatedEntrepreneurshipRegional scienceRegional innovation systemGovernment (linguistics)Regional developmentIntervention (counseling)LocationEconomic geographySmall islandInnovation systemEconomic growthGeographyBusinessEconomyEconomics

Abstract

fetched live from OpenAlex

The Northern Review 45 (2017): 33–56 https://doi.org/10.22584/nr45.2017.003This article provides an exploratory examination of the innovation dynamics in northern Canada, situated within the broader literature on staples theory, regional development, and regional innovation systems. It uses a case study on the mining innovation system in Greater Sudbury, Ontario—one of the most advanced regional innovation systems in northern Canada—to highlight the importance of innovation support institutions, government intervention, and building on competitive advantages. The article also explores a number of geographic, social, and economic challenges that can hinder entrepreneurship, innovation, and, ultimately, economic development in regions across the North. These include geographic remoteness and isolation, small and often sparsely populated regions, and development approaches that do little to facilitate the reinvestment of resource wealth back into regional development.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.059
GPT teacher head0.207
Teacher spread0.149 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it