Sustaining the sisterhood: Soul Sisters Pakistan (SSP)
Bibliographic record
Abstract
Learning outcomes The learning outcomes of this case study are to understand and apply the PESTLE framework with a special focus on sociocultural nuances of a conservative society, appreciate the role of innovation and effective leadership in the success of entrepreneurial ventures, understand the bricolage theory to critically evaluate the role of entrepreneurs as agents of social change and develop monetization strategies for digital start-ups and recommend strategies that would help social enterprises to strike the right balance between their social aspirations and commercial goals. Case overview/synopsis In March 2020, Kanwal Ahmed, founder of the much-lauded Facebook group Soul Sisters Pakistan (SSP), was posed with a critical situation. SSP’s first face-to-face member meetup, which had been hyped up by Pakistanis residing in Canada for months, had to be called off due to the advent of COVID-19. What worried Ahmed was not just the immediate impact of the postponement; rather, she was more concerned about how her social enterprise would sustain in the longer run. The new normal had changed the way businesses operated; tried and tested revenue generation strategies of SSP would neither be feasible in a COVID-stricken world nor reap the same results. Ahmed knew that her social enterprise could have a far-reaching impact in a pandemic-stricken world. However, she was unsure about how to monetize her business model so as to ensure steady revenue generation streams that would keep the enterprise afloat. Ahmed knew that the clock was ticking, and she had to act quickly and think of ways to ensure SSP’s long-term sustenance. Complexity academic level This case study is suitable for undergraduate students enrolled in courses of entrepreneurship and strategy. Supplementary materials Teaching notes are available for educators only. Subject code CSS 3: Entrepreneurship.
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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 | 0.001 | 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 | 0.018 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 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".