The door swings in and out: The impact of family support and country stability on success of women entrepreneurs in the Arab world
Bibliographic record
Abstract
Women-owned businesses represent a significant segment of the contemporary economy upon a global basis. However, women entrepreneurs still experience more obstacles than men depending on cultural context; for example, research on the Arab world concerning the interaction between women entrepreneurs and their families remains under-developed. Consequently, we ground our study upon an enhanced framework of agency theory, which includes family altruism. We examined the relationships between business-family interface (BFI) enrichment components and the performance of firms headed by female entrepreneurs women in Jordan and Sudan. Specifically, we investigated if and how the country level of political and social stability moderates these relationships. The findings suggest that the relationship between the family-related objective factor (family financial support) and the performance of firms headed by female entrepreneurs is not affected by the country’s political and social stability context. Conversely, the family-related subjective factor (family moral support) is affected by this context. Our study bridges the gap in contextual studies on the Arab world concerning the success of women-owned businesses and confirms how institutional elements affect business in addition to family-related matters. Implications for future research and public policy are discussed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".