Strategic Capabilities of Ghanaian Female Business Owners and the Performance of their Ventures [mimeo
Bibliographic record
Abstract
For some time now, women have been starting businesses at a rate more than twice that of men. Globally, women-owned businesses constitute between a quarter and a third of all businesses. While little empirical research has addressed women-owned businesses, even fewer studies have addressed women-owned businesses in Africa. Using the resource-based theory, this study reports the correlates of the performance of ventures owned by Ghanaian women. More specifically, the study focuses on the strategic, firm-level factors related to business performance. We hypothesise that performance of women-owned businesses is affected by strategic planning, the resources of the business, the skill and previous experience of the owner. The data for this study were collected in Ghana from June to August 2003. Subjects for the study were randomly selected from databases held by a quasi government organization and two women’s business organizations. The data were collected by eleven University of Ghana and nine Cape Coast University students after a one day orientation facilitated by the first author. During the first half of the day, interviewing skills and the duties of the
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".