Unravelling Challenges Hindering Female Successors within Family Passenger Transport Businesses in Mutare District, Zimbabwe
Bibliographic record
Abstract
Nowadays women empowerment has been increasing so rapidly all over the world and women are starting their own businesses to seek greater control over their personal and professional lives.Studies show that the experience of women in business is different from those of men.There are profound gender differences in both women experiences of business ownership and the performance of womenowned firms (Carter, Anderson & Shaw, 2001).According to Maas and Herrington, (2006) as cited in the International Trade Centre (2004), Canada has experienced a 200% growth in the number of women entrepreneurs over the last 20 years.Women-owned businesses, as reviewed by statistics in the USA, are the fastest growing sector of new business start-ups, with black women"s business forming a larger share of black-owned businesses than white-owned women"s businesses (Mattis, 2004).Within the African context, taking Cameroon as an example, women entrepreneurs manage 57% of small and microbusinesses.While in Uganda women entrepreneurs form the majority of the country"s businesspeople in the areas of farming and small to medium-sized enterprises.Women entrepreneurs in South Africa remain on the side-lines of the national economy.Most women in business in South Africa are concentrating in the areas of crafts, hawking, personal services and the retail sector.Only a few women entrepreneurs are participating in value-adding business opportunities (Maas & Herrington, 2006).However, there is dearth of literature of women successors participating in the transport sector, hence a gap has been created for this study to find the pushing factors that do not attract African women to be entrepreneurs in the family business, particularly in Manicaland province.Women-owned enterprises have their fair share of challenges and constraints that need to be addressed and specific needs have to be identified to help them perform at par, if not better, than their male counterparts in the transport business sectors as family successors.The challenges that women entrepreneurs face in Zimbabwe have not been adequately studied and developed.This study focuses on the constraints faced by African women business successors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".