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Record W2995459834 · doi:10.1111/grow.12353

An infatuation with building things: Business strategies, linkages, and small city economic development in Manitoba

2019· article· en· W2995459834 on OpenAlexaboutno aff
Murray D. Rice, Ronald V. Kalafsky

Bibliographic record

VenueGrowth and Change · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
FundersUniversity of North Texas
KeywordsInfatuationLocal economic developmentContext (archaeology)Small businessEconomic geographyRegional scienceBusinessBusiness developmentGovernment (linguistics)Local governmentEconomic growthMarketingGeographyEconomics

Abstract

fetched live from OpenAlex

Abstract The establishment of a solid understanding of regional economic development has proved to be highly elusive. Research efforts within this area have focused largely on major urban areas, yet this somewhat narrow focus means that economic development activities in smaller urban centers have not received the attention that they deserve. This article investigates regional economic development within a small city context through a survey‐based study of the entrepreneurial ecosystems operating in two small cities in the province of Manitoba. The results indicate that many currently accepted bases of regional business community expansion, such as government support and development of local suppliers, have limited utility within these cities. Concurrently, business leader survey responses from the two cities reveal a unique set of factors that drive economic development success in this nonmetropolitan case study, keyed by the pivotal role of a unique mix of nonlocal linkages, local cultural resources, and social connections in catalyzing local business expansion. These findings indicate that business community growth in the study cities proceeds from a distinctive template relative to larger centers, and suggest that increased research attention is necessary to elucidate the bases of business success in a more diverse selection of successful small cities.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.087
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.057
GPT teacher head0.253
Teacher spread0.196 · 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.

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
Published2019
Admission routes1
Has abstractyes

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