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Record W2978042955 · doi:10.1108/jepp-04-2019-0034

Growing entrepreneurial ecosystems

2019· article· en· W2978042955 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Entrepreneurship and Public Policy · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Development and Policy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIntermediaryEntrepreneurshipOriginalityVariety (cybernetics)Process (computing)BusinessIndustrial organizationKnowledge managementProcess managementMarketingComputer sciencePolitical scienceCreativity

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to illustrate experimentation over time in Ontario, Canada with place-based innovation policies to support the development and coordination of entrepreneurial ecosystems on a regional basis across the province. Design/methodology/approach Tracing the policy learning process and successive adaptations in program design over time, the authors provide a detailed case study of the evolution of the Ontario Network of Entrepreneurs (ONE) from 2003 to the present. Findings The authors find that the program has evolved in response to regular program reviews that include broad input from ecosystem actors operating at multiple levels within the network, and that intermediaries are key facilitators of inter- and intra-ecosystem linkages. However, program complexity and coordination challenges suggest that place-based innovation policies, such as the ONE, should focus specifically on innovation-intensive entrepreneurship. Research limitations/implications These findings make three contributions to the theory and practice of place-based innovation policy. First, these policies are by nature experimental because they must be able to flexibly adapt according to policy learning and practitioner input from a wide variety of local contexts. Second, multilevel interactions between provincial policymakers and regional ecosystem actors indicate that place-based innovation policy is neither entirely driven by “top down” policy, nor “bottom up” networks but is rather a complex and variable “hybrid” blend of the two. Finally, publicly funded intermediaries perform essential inter- and intra-ecosystem connective functions but system fragmentation and “mission creep” remain enduring policy challenges. Originality/value The paper makes an original contribution to the literature by analyzing the development of entrepreneurial policy support framework and situating the case study in the context of the policy learning process involved in place-based innovation policymaking in North America.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.958
Threshold uncertainty score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.024
GPT teacher head0.295
Teacher spread0.271 · 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