Intellectual Property Rights, Biotechnology and Discourses of Development: Internal Contradictions and Forms of Resistance
Bibliographic record
Abstract
The International Covenant on Economic, Social and Cultural Rights identifies freedom from hunger and malnutrition as a fundamental human right of every individual. The current global food crisis undermines this right and has multi‐faceted repercussions for poverty reduction and sustainable development in the Global South. A plethora of explanations have been proposed regarding the causes of the current food crisis, while a biotechnological solution involving the expansion of Genetically Modified (GM) seeds in the Global South has gained renewed momentum and simultaneously increased resistance. This presentation will provide a nuanced understanding of the promotion of IPRs and biotechnological ‘inventions’ as contemporary facets of a hegemonic modernization discourse of development. By first critically examining the development of IPRs and their relation to biotechnology I provide a basis for understanding the internal contradictions of this technologically reductionist discourse. Using a detailed case study from India, I then illustrate the way in which the internal contradictions of this discourse result in particular forms of resistance which significantly challenge the structure of the global food system.
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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 | 0.021 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.013 | 0.125 |
| Scholarly communication | 0.026 | 0.019 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.007 | 0.010 |
| 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".