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Record W4391120307 · doi:10.7202/1108480ar

Economic Development and Canada’s Gateways: A Tale of Two Regional Development Agencies

2024· article· en· W4391120307 on OpenAlexafffundvenueabout
Khadeja Elsibai, Jean Michel Montsion, Claudia De Fuentes, Peter Hall, Dorval Brunelle

Bibliographic record

VenueCanadian Journal of Regional Science · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Development and Policy
Canadian institutionsUniversité du Québec à MontréalSimon Fraser UniversityYork University
FundersAtlantic Canada Opportunities AgencyRural Development AdministrationAustralian Government
KeywordsGateway (web page)MindsetPolitical scienceEconomic growthGovernment (linguistics)Regionalism (politics)Agency (philosophy)Public administrationCentralityAsia pacificBusinessInternational tradeSociologyEconomicsPoliticsDemocracy

Abstract

fetched live from OpenAlex

The Atlantic Canada Opportunities Agency (ACOA) and Western Economic Diversification Canada (WD) are regional development agencies (RDAs) created to forge links between federal economic development priorities and local interests. RDAs in Canada follow a pro-trade agenda in support of local economic growth, but their strategies were adjusted in the 1990s to a new regionalism mindset, which emphasizes decentralized and collaborative leadership. In this article, we examine how both agencies responded, respectively, to the 2007 federal designation of an Atlantic Gateway on the East Coast, and an Asia Pacific Gateway on the West Coast. We combine a content analysis of each RDA’s yearly reports from 2007 to 2020, with a network analysis of their involvement in gateway projects funded by the federal government during this period. The combined analyses show the centrality of ACOA in gateway initiatives in Atlantic Canada, and the peripheral role of WD in Asia Pacific gateway initiatives.

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)0.004
metaresearch head score (Gemma)0.010
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.119
Threshold uncertainty score0.867

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.010
Science and technology studies0.0240.014
Scholarly communication0.0130.004
Open science0.0010.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.043
GPT teacher head0.287
Teacher spread0.244 · 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

Citations1
Published2024
Admission routes4
Has abstractyes

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