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Record W2241303939 · doi:10.22004/ag.econ.132288

Assessing the Growth of the New Economy across Canadian Cities and Regions: 1990-2000

2004· article· en· W2241303939 on OpenAlexaffabout
Desmond Beckstead, Mark Brown, Guy Gellatly, Catherine Seaborn

Bibliographic record

Venue˜The œjournal of regional analysis & policy · 2004
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional Economics and Spatial Analysis
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsUrban hierarchyMetropolitan areaEconomies of agglomerationEconomic geographyEconomyEmpirical researchHierarchyUrbanizationTechnological changeEconomicsGeographyEconomic growthMarket economyPopulation

Abstract

fetched live from OpenAlex

Economic analysts have expressed significant interest in the transition of the industrial base towards knowledge-intensive production. A central aspect of this transition is the growth and development of industries that provide the technological and scientific foundations for what is often termed the New Economy. This empirical study develops a geographic profile of New Economy industries in Canada across the urban/rural hierarchy and in different metropolitan areas between 1990 and 2000. The study also investigates whether measures of agglomeration economies are correlated with the increased incidence of New Economy industries across different locations over the study period. The study shows that the employment growth in New Economy industries through the 1990s has been primarily an urban phenomenon and that agglomeration economies have played an increasingly important role in the formation of these industries.

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)0.003
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 score0.041
Threshold uncertainty score0.297

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.009
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.256
Teacher spread0.228 · 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

Citations3
Published2004
Admission routes2
Has abstractyes

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