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Record W2119298547 · doi:10.1142/s0218495807000071

STAGES OF SMALL ENTERPRISE DEVELOPMENT: A COMPARISON OF CANADIAN FEMALE AND MALE ENTREPRENEURS

2007· article· en· W2119298547 on OpenAlexaffabout
J. Terence Zinger, Rolland LeBrasseur, Yves Robichaud, Nathaly Riverin

Bibliographic record

VenueJournal of Enterprising Culture · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsLaurentian University
Fundersnot available
KeywordsEntrepreneurshipContext (archaeology)Small businessWomen entrepreneursFemale entrepreneursBusinessDemographic economicsMarketingVariety (cybernetics)Business developmentEconomicsBiologyFinance

Abstract

fetched live from OpenAlex

The explosive growth in the rate of new business formation by women has spurred renewed research interest in the area of female entrepreneurship and its related economic impact. Yet, there has been a dearth of research into the influence of gender on new venture formation and development. This study draws on data from the annual survey of the Global Entrepreneurship Monitor to examine the differences between female and male entrepreneurs in the early stages of small enterprise development. The data was aggregated for the period 2002 through 2004, and consisted of 444 Canadian entrepreneurs: 164 females and 280 males. Gender differences are explored within the context of a variety of personal as well as business-related variables. Women entrepreneurs had a much greater propensity to have established a consumer or business services enterprise, and reported significantly lower income levels. In addition, they were less likely than their male counterparts to work full time at their business, to utilize new technology or to anticipate new business opportunities in the near term. In terms of the enterprise's stage of development, it was found that 62 percent of the enterprises operated by females were ‘nascent’ small firms, while 38 percent were ‘new;’ the respective proportions for males were 55 percent and 45 percent. The analysis revealed that the difference between genders on business-related variables strengthens as the firm evolves through the stages of development from nascent to new; however, there was mixed support for the corollary hypothesis that differences in personal characteristics and attitudes diminish during this progression: even for ventures that have reached the ‘new’ phase, personal variables continue to act as important discriminators between genders. The paper provides a discussion of the implications of these empirical findings, as well as some directions for future research.

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 score0.032
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.025
GPT teacher head0.258
Teacher spread0.233 · 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

Citations24
Published2007
Admission routes2
Has abstractyes

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