Emerging Ghanaian and Nigerian Fashion Entrepreneurs: The Cultural considerations and Structural Challenges of Growing a Fashion Business in a Developing Economy
Bibliographic record
Abstract
In 2016, Ghana’s capital city of Accra, located along the Atlantic coast, was touted as “Africa’s Capital of Cool” by the New York Times (July 2016), highlighting the growing number of boutiques, hotels and world-class restaurants. Just a couple of months earlier, on April 30, 2016, the Brighton Museum & Art Gallery had opened the first major UK exhibit dedicated to African Fashion. The book Fashion Cities Africa, edited by Eritrean-born journalist Hannah Azieb Pool, was released the same month, and shares insights into the aesthetics and designs emerging from Nairobi (Kenya), Casablanca (Morocco), Lagos (Nigeria) and Johannesburg (South Africa). Since the start of the millennium, fashion journalists (Suzy Menkes and André Leon Talley) have been discussing the prevalence of high-end African fashion designers such as Duro Olowu, Lisa Folawiyo, and Folake Folarin Coker.
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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 | 0.002 | 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 | 0.009 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".