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Functional specialization across space: a case study of the Canadian Electricity Industry, 1971–2001

2008· article· en· W2014176769 on OpenAlexafffundvenueabout
Cédric Brunelle, Mario Polèse

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional Economics and Spatial Analysis
Canadian institutionsInstitut National de la Recherche Scientifique
FundersCanada Research Chairs
KeywordsMetropolitan areaDistribution (mathematics)Economic geographyElectricity generationElectricitySpace (punctuation)Biomass (ecology)GeographyProduction (economics)Fossil fuelPower (physics)EconomicsEcologyMicroeconomicsEngineeringMathematicsComputer scienceBiology

Abstract

fetched live from OpenAlex

This article examines the location of functions within the electricity sector in Canada from 1971 to 2001, using a centre‐periphery model. Power generation, distribution and retailing are generally carried out by multiestablishment crown corporations. Location patterns of different functions—management, scientific, production, etc.—are analyzed via the use of occupational groups. The spatial distribution of functions is found to be generally consistent with centre‐periphery relationships, with evidence of a growing functional specialization between large metropolitan and nonmetropolitan locations. However, differences emerge depending on power generation sources: fossil fuels, hydro, nuclear, solar or biomass. The choice of a power generation source has consequences for local economies.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.053
Threshold uncertainty score0.385

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.013
Science and technology studies0.0070.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.035
GPT teacher head0.206
Teacher spread0.171 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations6
Published2008
Admission routes4
Has abstractyes

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