Situating Political Agronomy: The Knowledge Politics of Hybrid Rice in India and Uganda
Bibliographic record
Abstract
ABSTRACT The emergence of ‘political agronomy’ — a research agenda that interrogates the knowledge politics through which agronomic debates are constructed, shaped and contested — has added a new and important tool for the analysis of agricultural research and policy making in development contexts. This article seeks to advance the scope of political agronomy by providing an enhanced framework to link the analysis of agronomic knowledge production to the study of new agricultural technologies in practice. Using case studies of hybrid rice promotion in southern India and western Uganda, the article illustrates the power relations and unanticipated outcomes that accompanied the translation of agronomic research into agrarian settings characterized by pronounced social polarization and marked environmental transformations. These case studies affirm how the starkly uneven outcomes of technological change refract back into the politics of agronomic research and extension as both researchers and policy makers react to the unintended impacts of previous interventions when designing future agendas.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.015 | 0.037 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".