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Record W4415586550 · doi:10.21083/crrf.v29i1.7716

WorkingTogether to Build a Regional Innovation Ecosystem in Non-Metropolitan Areas: BC Insights

2025· article· W4415586550 on OpenAlexaffabout
Jennifer Tedman-Jones, Amber Hayes, Erin Handy, Terri MacDonald, Lukas Bichler

Bibliographic record

VenueProceedings of the Canadian Rural Revitalization Foundation · 2025
Typearticle
Language
FieldSocial Sciences
TopicRegional Development and Policy
Canadian institutionsSelkirk CollegeKootenay Association for Science & TechnologyMitacsUniversity of British Columbia, Okanagan Campus
Fundersnot available
KeywordsRegional developmentResource (disambiguation)Key (lock)Regional innovation systemRange (aeronautics)Human resourcesRegional policy

Abstract

fetched live from OpenAlex

British Columbia is a large province with a diverse range of geographic regions, communities and cultures; the province’s economy is equally diverse, with economic development dependent on a range of industries and businesses. Like many parts of non-metropolitan Canada, the BC Interior region faces a number of challenges in meeting the demands of the 21st century economy, including those associated with transforming and diversifying the regional resource economy to one driven by innovation. To help understand and navigate these challenges and opportunities, BC is fortunate to have significant expertise and leadership in regional socio-economic innovation and socio-economic development research embedded within its non-metropolitan areas. This panel, comprised of key researchers and leaders in BC’s regional innovation ecosystem, will share their experiences in helping make the BC Interior the optimal living lab for regional innovation, and offer insights on the important role non-metropolitan areas can and must play for Canada to move toward a more innovative and inclusive economy.

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.799
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.011
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.018
GPT teacher head0.290
Teacher spread0.272 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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