The Ethics of Introducing <scp>GMOs</scp> into sub‐<scp>S</scp>aharan <scp>A</scp>frica: Considerations from the sub‐<scp>S</scp>aharan <scp>A</scp>frican Theory of <i><scp>U</scp>buntu</i>
Bibliographic record
Abstract
A growing number of countries in sub-Saharan Africa are considering legalizing the growth of genetically modified organisms (GMOs). Furthermore, several projects are underway to develop transgenic crops tailored to the region. Given the contentious nature of GMOs and prevalent anti-GMO sentiments in Africa, a robust ethical analysis examining the concerns arising from the development, adoption, and regulation of GMOs in sub-Saharan Africa is warranted. To date, ethical analyses of GMOs in the global context have drawn predominantly on Western philosophy, dealing with Africa primarily on a material level. Yet, a growing number of scholars are articulating and engaging with ethical theories that draw upon sub-Saharan African value systems. One such theory, Ubuntu, is a well-studied sub-Saharan African communitarian morality. I propose that a robust ethical analysis of Africa's agricultural future necessitates engaging with African moral theory. I articulate how Ubuntu may lead to a novel and constructive understanding of the ethical considerations for introducing GMOs into sub-Saharan Africa. However, rather than reaching a definitive prescription, which would require significant engagement with local communities, I consider some of Ubuntu's broader implications for conceptualizing risk and engaging with local communities when evaluating GMOs. I conclude by reflecting on the implications of using local moral theory in bioethics by considering how one might negotiate between universalism and particularism in the global context. Rather than advocating for a form of ethical relativism, I suggest that local moral theories shed light on salient ethical considerations that are otherwise overlooked.
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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 | 0.012 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.032 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| 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".