Dynamics of entrepreneurial belonging among Mexican female entrepreneurs
Bibliographic record
Abstract
Purpose Understanding belonging provides a better insight into the structural, political, cultural and gendered elements of entrepreneurship. This paper aims to focus on Mexican female entrepreneurs’ (MFE) experiences in managing material and affective aspects of entrepreneurial belonging during the start-up and transition phase to become an established business owner. Design/methodology/approach The narrative analysis is based on qualitative interview data with 11 MFE in Mexico. Findings The analysis reveals that MFEs’ sense of belonging evolves from self-oriented to more socially-oriented identity claims. In the former, the need to “fit in” and achieve material aspects of belonging is intertwined with gender and family responsibilities. In the latter, the need to “stand out” and achieve affective aspects of belonging is intertwined with validating entrepreneurial achievements by challenging gendered assumptions and helping others through the notion of “sisterhood.” Originality/value The paper extends the understanding of the relation of material and affective aspects of belonging as an “evolving” process from the nascent stage to the established stage of entrepreneurship. Within the evolving process of entrepreneurial belonging, a shift from material to affective aspects unveils a theoretical framework that relates belonging, gender and entrepreneurship in context. This process seems to regulate entrepreneur’s agency in what they interpret as acceptable while standing up against challenges and legitimizing belonging through the emergence of a “sisterhood.”
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".