MétaCan
Menu
Back to cohort
Record W2599843507 · doi:10.5539/ibr.v10n4p92

Fostering Entrepreneurship, Creativity and Innovation in Cities

2017· article· en· W2599843507 on OpenAlexvenueno aff
Elzo Alves Aranha, Neuza Abbud Prado Garcia, Paulo Henrique dos Santos

Bibliographic record

VenueInternational Business Research · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicUniversity-Industry-Government Innovation Models
Canadian institutionsnot available
Fundersnot available
KeywordsCreativityEntrepreneurshipTransformative learningContext (archaeology)SociologyValue (mathematics)ConstructiveReflexivityCreative cityProcess (computing)MarketingBusinessKnowledge managementComputer sciencePolitical science

Abstract

fetched live from OpenAlex

The aim of this study is to develop a new tool to foster entrepreneurship, creativity and innovation in cities. The tool consists of transformative dimensions, able to synthesize, assemble and embrace the notions of entrepreneurial city, creative and innovative. Then it seeks to illustrate the operation of the city model proposed taking into account 51 Cities Master Plans in Brazil. The study is exploratory and adopts a reflexive methodology. The main innovative result is the entrepreneurial city model tool which meets five essential transformative dimensions: value proposition, customers, value configurations, strategic partnerships and revenue model. The entrepreneurial city model tool proposed aims to increase the dynamics understanding of the procedural flow in the city context, from the entrepreneurial activity perspective. This process flows dynamics can be expressed in the city, for example, in the planning, implementation and actions monitoring, programs, projects and public policies directed to notions of entrepreneurial city, creative and innovative. The innovative results of this research have several practical implications, among which are: (1) public management in the city; (2) public policy makers; (3) researchers and scholars; (4) human resource professionals.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0010.002
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 head0.173
GPT teacher head0.363
Teacher spread0.190 · 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.

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

Citations2
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueInternational Business ResearchSame topicUniversity-Industry-Government Innovation ModelsFrench-language works237,207