Influence of Spirituality on Bitter Kola Consumption Among Pretoria Residents in Response to COVID-19 and Related Illnesses
Bibliographic record
Abstract
The agrarian continent of Africa has many fruits with nutritional, medicinal and spiritual values. Regardless, Africa leads the statistics of poor healthcare globally. Two major challenges in Africa’s healthcare system are poor access and the high cost of medical healthcare. Among others, the effects of such challenges include low responsiveness to medical treatment and a high mortality rate. However, it seems the nosophobia that accompanied the global mortality rate during the COVID-19 pandemic may have triggered a spiritually influenced alternative. One of the traditional alternatives was a subscription to Garcinia Kola, popularly known as Bitter Kola (BK). This article, majoring in spiritual and not psychological influence, raised a hypothetical question: does spirituality influence Africans’ traditional response to COVID-19? To answer this question, Sunnyside in Pretoria was chosen as a demography to investigate the hypothesis. Data were collected via mixed research methods. There were 16 qualitative respondents, including sellers, herbalists and clergies, and 75 consumers as quantitative respondents under probability sampling. The results analysed using Excel and Python’s regression analysis demonstrated strong connections between consumers’ spiritual motivations, the sales period, the sales rate, and the swift traditional response to the pandemic and related illnesses. The outcome validated the influence of spirituality on 60.9% of quantitative respondents and showed how 25–72% responded to COVID-19 symptoms with BK. Likewise, 87.5% of qualitative respondents consumed BK via indigenous spiritual knowledge in response to the pandemic. Subsequently, this article discussed the benefits, limitations and lessons of spiritual influence on BK consumption in the post-COVID-19 era.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".