A non-linear approach to the establishment of local biological control agent production units: a case study of fall armyworm in Bangladesh
Bibliographic record
Abstract
Abstract Background Strides have been made in Bangladesh to promote the utilisation of biological control agents (BCAs), however farmer utilisation remains sub-optimal. The establishment of local BCA production hubs, although touted as a panacea to this problem, has no proven business case. This study makes the case for a non-linear business model. Methods Qualitative and quantitative data from maize growing areas in Bangladesh was collected via telephone interviews from key informants representing four key stakeholders—national research institute, regional research stations, farmer producer organisations and agro-dealers. Results Farmer uptake of BCAs in Bangladesh for FAW management is hindered by several factors—lack of BCAs availability in local markets, negative farmer and agro-dealer perceptions, poor input industry linkages for the supply of BCAs products to agro-dealers and inadequate institutional finances for capacity building of and technical support by research scientists and extension agents. Given these challenges to BCAs uptake, an innovation systems-based business model that links researchers, extensionists, agro-dealers and farmer producer organizations in a non-linear pathway is proposed for Bangladesh. This translates into the establishment of local BCA production hubs owner-managed by farm entrepreneurs, with scientists providing them with nucleus culture, while extension services provide technical support for quality assurance. The interaction between all stakeholders is non-linear with all actors intellectually consulted and engaged, with technical capacity on BCAs available for any actor requiring it. Multi-disciplinary research, that takes into account feedback from stakeholders, complements the process thus generating robust and relevant knowledge for feedbacking to improve the business model, capacity building initiatives and farmer engagement. Conclusions Mentoring and capacity building leveraged via engagement of research institutions; and demonstration of technology use and guidance utilising extension services and agro-dealer networks, will promote the utilisation of BCAs for FAW management and enable local farm entrepreneurs to meet the increased demand via establishment of local BCA production hubs.
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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 | 0.003 | 0.004 |
| 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 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".