Banati foundation: using marketing to empower girls at risk and diminish the stigma associated with homelessness
Bibliographic record
Abstract
Research methodology To write this case, several research methods were used. Most importantly, field interviews were conducted with employees at Banati foundation. The interviews were held with three different employees at different points in time, including the marketing manager, the executive manager and the head teacher working with the girls at the foundation. These interviews helped provide details regarding the foundation’s culture which is hard to get from secondary sources. In addition to this, one of the researchers was a volunteer at the foundation for 6 months before starting this research and so had strong background knowledge on the workings of the entity. Finally, secondary sources were used to provide accurate historical information and numerical statistics. These sources included the foundation’s website and annual reports as well as newspaper interviews with the Banati’s Chairperson. Case overview/synopsis This case poses the marketing dilemma faced by Banati Foundation, a non-profit organization (NPO) based in Egypt. Banati has offered child protection services to girls at risk since its establishment in 2009. In particular, the case focuses on the foundation’s strategy and operations in 2020. Since its inception, the foundation has been led by the main founder, Dr Hanna Abulghar. Under her leadership, the foundation flourished and won several international awards. The foundation became a home, a school and a support system to the girls who were once homeless. Yet even though Banati succeeded in improving the lives of many girls at risk, the foundation still sought ways to sustain its funds and to empower the girls to thrive after they left the foundation. As the key person responsible for setting the foundation’s direction and strategy, Dr Hanna faced marketing challenges that include overcoming social stigma, diversifying the donor base and increasing fundraising. Complexity academic level This case is suitable for undergraduate and Master’s students who already have an understanding of the basic marketing principles such as the marketing mix (4Ps)/market segmentation and have taken an introductory marketing course previously. Furthermore, the case presents an opportunity to apply marketing concepts such as segmentation, targeting, positioning and promotion within the context of social and NPO marketing. It is ideal for students studying social marketing, NPO marketing strategy, cause marketing, fundraising techniques and social inclusion.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.008 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".