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Marshaling Resources to Form Small New Ventures: Toward a More Holistic Understanding of Entrepreneurial Support

2007· article· en· W2024733301 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.

Bibliographic record

VenueEntrepreneurship Theory and Practice · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsUniversity of CalgaryMemorial University of Newfoundland
Fundersnot available
KeywordsMarshallingResource (disambiguation)Sample (material)BusinessQuality (philosophy)Key (lock)EntrepreneurshipKnowledge managementResource-based viewMarketingNew VenturesCore (optical fiber)Resource mobilizationConceptual frameworkIndustrial organizationSociologyComputer scienceCompetitive advantagePolitical scienceSocial science

Abstract

fetched live from OpenAlex

This article makes two contributions to our understanding of the core entrepreneurial activity of assembling resources to pursue an opportunity. First, a conceptual framework is presented to organize the research on resource mobilization. Second, a study is presented based upon interviews with a random sample of 48 entrepreneurs to identify the supporters whom the entrepreneurs considered to have been key to their success and the resources obtained from these individuals. Results indicate that maximizing the overall effectiveness of resource combinations is a complex undertaking involving trade–offs between the quantity and quality of available resources and the efficiency versus effectiveness of supporters.

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)0.004
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.083
GPT teacher head0.310
Teacher spread0.227 · 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