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Trustworthiness: A Critical Ingredient for Entrepreneurs Seeking Investors

2011· article· en· W2126206003 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 · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPrivate Equity and Venture Capital
Canadian institutionsYork UniversityUniversity of Waterloo
Fundersnot available
KeywordsTrustworthinessSoftware deploymentInvestment (military)BusinessControl (management)Affect (linguistics)Empirical researchInvestment decisionsMarketingMicroeconomicsEconomicsPsychologySocial psychologyBehavioral economicsFinanceLawManagementComputer science

Abstract

fetched live from OpenAlex

We investigate how an entrepreneur's behaviors during an initial interaction with a business angel can build, damage, or violate trust, and how the investor's level of trust (prompted by the entrepreneur's behavior) can affect his/her decision to make an investment offer. Our empirical analysis shows that entrepreneurs who receive offers from business angels exhibit a larger number of trust–building behaviors during the initial interaction and a smaller number of unintentional trust–damaging behaviors than those who do not receive an offer, and display few deliberate trust–violating behaviors. We further observe that the investor's deployment of a control mechanism is a prerequisite for receiving an investment offer for all entrepreneurs who damage or violate trust.

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)0.003
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
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 score0.234
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.003
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 head0.060
GPT teacher head0.286
Teacher spread0.225 · 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