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Record W4281571492 · doi:10.1108/ijge-10-2021-0169

Does mentoring reduce entrepreneurial doubt? A longitudinal gendered perspective

2022· article· en· W4281571492 on OpenAlexaff
Étienne St-Jean, Amélie Jacquemin

Bibliographic record

VenueInternational Journal of Gender and Entrepreneurship · 2022
Typearticle
Languageen
FieldPsychology
TopicMentoring and Academic Development
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsDyadEntrepreneurshipOriginalityPerspective (graphical)Value (mathematics)PsychologySocial psychologyStereotype (UML)SociologyPolitical scienceCreativity

Abstract

fetched live from OpenAlex

Purpose Mentoring appears to be a good support practice to reduce entrepreneurial doubt, amongst other things. Although perceived similarity could foster the mentoring relationship, gender dyad composition may also influence doubt reduction for entrepreneurs because of the potential gender stereotype in entrepreneurship. Design/methodology/approach The authors performed longitudinal research based on an initial sample of 170 entrepreneurs supported by a mentor to investigate the evolution of entrepreneurial doubt. Findings This study demonstrates that doubt can be reduced with mentoring, but only temporarily for male mentees. Gender stereotypes may be at play when it comes to receiving the support of a female mentor as entrepreneurship is still, unfortunately, a “male-dominated world.” Receiving support from mentors perceived as highly similar within the dyad does not reduce entrepreneurial doubt. Trusting the mentor is an important aspect, besides gender, in reducing entrepreneurial doubt. Originality/value The research provides insights into the gendered effect of mentoring to reduce entrepreneurial doubt. It shows that gender dyad composition should be taken into consideration when studying mentoring or other similar support to entrepreneurs.

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)0.001
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 score0.238
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.064
GPT teacher head0.348
Teacher spread0.284 · 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

Citations12
Published2022
Admission routes1
Has abstractyes

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