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Record W3086249967 · doi:10.1177/1042258720952288

Regional Path Breaking: The Role of Industry Switching, Industry Diversity, and New Knowledge in New Venture Exit

2020· article· en· W3086249967 on OpenAlexaff
Lawrence A. Plummer, Simon C. Parker, Silvia Carolina Reyes

Bibliographic record

VenueEntrepreneurship Theory and Practice · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional Economics and Spatial Analysis
Canadian institutionsWestern University
Fundersnot available
KeywordsEconomic geographyCompetition (biology)BusinessMetropolitan areaIndustrial organizationDiversity (politics)Path dependencePath (computing)Spawn (biology)EconomicsMicroeconomicsPolitical scienceGeography

Abstract

fetched live from OpenAlex

Regions with spatial concentrations of businesses create conditions that spawn new firms, but also undercut new venture survival. Localized competition puts pressure on new firms to exit. Adding to this pressure to exit is regional path dependence, which limits the ability of firms to respond strategically to hostile local conditions. We investigate the extent to which the pressure to exit created by localized competition is moderated by three “path breaking” factors—new knowledge, industry diversity, and industry switching. We test and find broad support for our hypotheses using data from 355 metropolitan statistical areas in the United States spanning 2002 to 2010.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.227
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.069
GPT teacher head0.254
Teacher spread0.186 · 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 designTheoretical or conceptual
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

Citations12
Published2020
Admission routes1
Has abstractyes

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