Bibliographic record
Abstract
This study focussed on developing a strategy framework for sustainable business undertaking by black women owned cooperatives in the Northern Cape district of Francis Baard. Black women owned cooperatives face a number of notable impediments that obstruct sustainable and successful business development and management. Some of the contributors to the current state of affairs could be attributable to lack of effective strategy focussed on cooperatives in general and black owned women cooperatives in particular. A number of studies have been published on the plight and status of cooperatives in South Africa and beyond, with clearly focussed recommendation emanating from empirical findings. This study, being aware of vast repository of literature on the phenomena and using the Population, Intervention, Comparator and Outcome (PICO) method, sought to answer the question, “how to develop a strategy framework for black women owned cooperatives to run sustainable businesses. A Qualitative Evidence Synthesis, a method within the Systematic Reviews approach was adopted as suitable orientation for answering the research question. A systematic review, also known as research on research (RoR) provides evidence based solution hinged upon primary research conducted by many different authors on the same context or situation. Using a Preferred Reporting items for systematic Reviews and Meta-Analysis (PRISMA), A total of 400 articles were retrieved from varied databases such as Ebsco-host, Google Scholar, Z-Library and Web of Science. Through a rigorous critical appraisal of these articles, 100 articles were finally included in the study as subject of analysis. Thematic analysis using the webQDA software produced thematic expressions that were finally treated to develop a theory/framework as per main research objective. The outcome of this qualitative evidence synthesis culminated in a formulation of the SNI Framework for Sustainable Black Women Owned Cooperatives.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.049 | 0.007 |
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".