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Record W4392820635 · doi:10.59876/a-bn7v-8q6j

Female and Male Entrepreneurs' Managerial Behaviour: A Brazilian Study

2002· article· en· W4392820635 on OpenAlexvenueno aff
Hilka Pelizza Vier MACHADO, Fernando Antônio Prado Gimenez, Valdir GOMES, Lilian Aligleri, Cleufe Pelisson, Luiz Antonio Aligleri

Bibliographic record

VenueManagement international · 2002
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsnot available
Fundersnot available
KeywordsEntrepreneurshipDiversity (politics)Style (visual arts)SociologyPsychologyDemographic economicsSocial psychologyGeographyPolitical scienceEconomics

Abstract

fetched live from OpenAlex

In the last two decades a large number of papers have investigated gender and its relationship to entrepreneurial activities. Most of these studies analysed a small number of variables. In general, the results have not been very significant in terms of identifying differences between men's and women's entrepreneurial behaviour. Integrative perspectives involving a diversity of variables to explain entrepreneurial behaviour can represent an important contribution to studies of this nature. Our purpose in this paper, which presents the results of an investigation conducted in two cities in Parana, a Southern Brazilian state, is to illustrate how this can be done. Results indicated similarities in male and female entrepreneurial behaviour in most of the variables studied in this piece of research. However, some significant differences were found, mainly associated with characteristics of managerial style, relationship with the market, and strategies adopted by the entrepreneurs. We conclude this paper with suggestions for future studies that can contribute to a better understanding of entrepreneurship. [PUBLICATION ABSTRACT]

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.019
GPT teacher head0.238
Teacher spread0.219 · 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 teacher head, not a consensus.

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

Citations8
Published2002
Admission routes1
Has abstractyes

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