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Record W3025616217 · doi:10.1504/ijesb.2017.10006398

Human capital, financial strategy and small firm performance: a study of Canadian entrepreneurs

2017· article· en· W3025616217 on OpenAlexaffabout
Carlos Raúl Sánchez Sánchez, Cälin Gurǎu, Amarjit Gill, Léo‐Paul Dana

Bibliographic record

VenueInternational Journal of Entrepreneurship and Small Business · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsDiversification (marketing strategy)BusinessFinanceProfit marginEntrepreneurshipCash flowReturn on investmentFinancial capitalHuman capitalInvestment (military)Profit (economics)EconomicsMarketingEconomic growthMicroeconomics

Abstract

fetched live from OpenAlex

This study investigates the relationship between human capital, financial strategy, and small firm performance in Canadian firms, analysing primary data collected through telephone surveys from 187 start-up owners. The results show that bank connections, entrepreneurial experience, internal financing sources, and investment motivations are positively correlated with the performance of small ventures; bank connections, entrepreneurial experience, personal financial sources, and risk diversification have a positive correlation with the net profit margin; while bank connections and the financial investment of immediate family members show a positive correlation with both return on investment and cash flow. The study enriches the literature concerning the factors affecting small firms' performance, exploring, both synthetically and analytically, the complex relationships between human, social and financial capital.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0070.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.255
Teacher spread0.212 · 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 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

Citations1
Published2017
Admission routes2
Has abstractyes

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