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Record W2060445174 · doi:10.1142/s0218495811000702

THE ROLE OF PARTNERSHIPS ON THE LEGAL STRUCTURE AND LOCATION CHOICE OF NASCENT SOCIAL VENTURES

2011· article· en· W2060445174 on OpenAlexaffabout
Moriah Meyskens, Alan L. Carsrud

Bibliographic record

VenueJournal of Enterprising Culture · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCommunity Development and Social Impact
Canadian institutionsToronto Metropolitan University
FundersFlorida International UniversityEwing Marion Kauffman Foundation
KeywordsSocial entrepreneurshipBusinessNew VenturesMarketingSocial enterpriseValue creationProfit (economics)Latin AmericansEmpirical researchPublic relationsEntrepreneurshipIndustrial organizationEconomicsFinancePolitical science

Abstract

fetched live from OpenAlex

Social ventures are organized as nonprofit, for-profit or hybrid organizations whose primary purpose is to address unmet social needs and create social value. Partnerships are one of the key strategies employed by social ventures to gain resources. This study focuses on evaluating the role of partnerships on nascent social ventures participating in business plan competitions. The results suggest that partnerships are more important for nonprofit and hybrid social ventures than for for-profit social ventures. Findings also suggest that partnerships are more essential for social ventures operating in developing regions such as Africa, Asia and Latin America where institutional constraints are greater than in the United States or Canada. This study provides some empirical insight into how partnerships impact nascent social ventures operating with distinct legal structures and in different locations of operation.

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)0.003
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.262
Teacher spread0.193 · 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 designQualitative
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

Citations10
Published2011
Admission routes2
Has abstractyes

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