Africa's “Seed” Revolution and Value Chain Constraints to Early Generation Seeds Commercialization and Adoption in Ghana
Bibliographic record
Abstract
The study aims to deepen understanding of how Early Generation Seeds value chain constraints impede commercialization and adoption of High Yielding Varieties (HYV) or improved Maize seeds by smallholders in Ghana within the broader strategies of a “Green Revolution for Africa”. Using qualitative and quantitative information obtained through one-on-one interviews with 15 key informants, a household survey from 110 smallholder farmers and document reviews, we discuss constraints and bottlenecks engendered by value chain structures, processes and mechanisms in Ghana's formal seed distribution system. Seven main challenges were identified that undermine trust and hinder the expansion of HYVs: (1) the limited capacity of public institutions, (2) constrained capacity of the emerging private sector, (3) a lack of well-defined, fair and enforceable contracts between stakeholders in the delivery system, (4) land-tenure limitations, (5) poor forecasting of farmers' demands for seeds by research institutions and seed producers, (6) sparse marketing arrangements for improved maize seeds, and (7) concentration of power to control seed supply in the hands of few institutions. We argue these seven issues weaken power asymmetry within the maize seed value chain's governance mechanism to create nodal points that give prominence to key public institutions, NGOs, and research institutions who control the production and distribution of improved seeds. Ultimately, trust among actors and its value chain outputs is undermined, negatively affecting the commercialization, availability, and adoption of improved seeds. Moving forward, upgrading the maize seed value chain must be pursued through targeted public and private sector relationships that acknowledge diverse actors' critical roles in the value chain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".