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Record W3091860734 · doi:10.1108/qrfm-03-2019-0034

Entrepreneurial microcredit support: the silver bullet for microenterprises success. The case of funds Mauricie in Quebec

2020· article· en· W3091860734 on OpenAlex
Ayi Gavriel Ayayi, Chantale Dalí

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueQualitative Research in Financial Markets · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsOriginalityEmpowermentSociologyMicrofinanceSocial constructivismEntrepreneurshipMarketingAutonomyKnowledge managementValue (mathematics)Public relationsQualitative researchEconomicsBusinessEconomic growthPolitical sciencePedagogySocial scienceComputer science

Abstract

fetched live from OpenAlex

Purpose This study aims to propose a model of entrepreneurial microcredit support that could address the problem of entrepreneurial support provided by microfinance institutions. This objective is justified by the need to produce scientific knowledge that could be of use to practitioners and political decision-makers who formulate and implement strategies of social inclusion and poverty reduction. Design/methodology/approach The study adopts a socio-constructivist research perspective. Social constructivism is a theoretical approach that posits that all social reality is constructed. In other words, individuals construct their knowledge of reality relative to their social setting. This justifies the use of the focus group to supplement and validate the data gathered in an individual interview. The socio-constructivist perspective allows us to better understand and develop knowledge based on the meaning that interviewees attribute to their experience. This perspective also justifies the choice of qualitative data collection method. The data were collected during semi-structured interviews. Findings Entrepreneurial microcredit support is distinguished from classic entrepreneurial support because it places the individual at the center of the process by emphasizing soft skills in the development of the entrepreneurial spirit. This approach engenders an efficient support process that comprises three main steps: determination of entrepreneurial potential, empowerment and reinforcement of autonomy and acquisition of managerial skills. The efficiency stems from the fact that the time factor is not a constraint in the entrepreneurial microcredit support process and from the relationship of proximity and trust between the credit agent and the micro-entrepreneur. Originality/value To the best of authors’ knowledge, this is the first paper to deal with the entrepreneurial microcredit support, which is completely different from the classical entrepreneurial support because of the uniqueness of microfinance and micro-entrepreneurs. The model clearly reveals that the support for the development of the skills required to successfully run a microenterprise is provided based on a socio-constructivist approach in which the micro-entrepreneur is the main actor in the construction of “mobilized knowledge” required to nurture promoters’ entrepreneurial spirit. Consideration of soft skills in a socio-constructivist perspective is, therefore, indispensable for entrepreneurial development.

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)0.004
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.105
GPT teacher head0.395
Teacher spread0.290 · 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