Entrepreneurial microcredit support: the silver bullet for microenterprises success. The case of funds Mauricie in Quebec
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".