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Record W2025556358 · doi:10.1080/09654310903491648

Understanding the Vancouver Hydrogen and Fuel Cells Cluster: A Case Study of Public Laboratories and Private Research

2010· article· en· W2025556358 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEuropean Planning Studies · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Development and Policy
Canadian institutionsGlobal Affairs CanadaSimon Fraser University
FundersSocial Sciences and Humanities Research Council of CanadaNational Research Council Canada
KeywordsState (computer science)Cluster (spacecraft)Work (physics)Regional sciencePolitical sciencePublic administrationBusinessEconomic growthEconomyEconomicsSociologyEngineering

Abstract

fetched live from OpenAlex

Conventional analyses of conventional industrial clusters look at the local, regional, 1 national and global factors affecting their ability to compete and grow. However, it is beginning to become apparent that in at least a few cutting-edge, high-technology areas, firms compete directly on a global basis for talent and markets. A case study of the fuel cell cluster in Vancouver, Canada appears to confirm this proposition. Policy makers have realized that this cluster must compete on the world market if it is to succeed. The cluster is endowed with several favourable factors including a high quality of life for its human capital and strong support for demonstration projects.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
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 head0.345
GPT teacher head0.424
Teacher spread0.079 · 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