Seeds of hope, seeds of despair: Towards a political economy of the seed industry in southern Africa
Bibliographic record
Abstract
The seed industry in Southern Africa has been radically transformed by a policy of liberalisation and privatisation started under structural adjustment. Traditionally under the domain of parastatals, seed research, production and distribution has been criticised for failing to provide modern variety seed to smallholder farmers. However, the private companies which have stepped in to replace seed parastatals in southern Africa have proven no more effective in meeting the demands of smallholders. The Trade Related Intellectual Property Rights (TRIPs) Agreement, concluded in 1994 as part of the Uruguay Rounds of GATT negotiations, as well as certain biotechnological innovations such as Terminator or Traitor technologies, threaten to further undermine local seed production and consumption by destroying the informal seed sector so central to agricultural production in the region. What alternatives exist? The success of Zimbabwe's maize seed network offers some insight. Resting on a unique relationship between government and nationally based producer co-operatives, Zimbabwe's maize programme was able to provide nearly every farmer in the country with hybrid maize suited for local growing conditions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".