Rhetorics and realities of participation: the Ethiopian agricultural extension system and its participatory turns
Bibliographic record
Abstract
We present a context-sensitive perspective on participation in rural development, revolving around the reconstruction of unique sets of differences between rhetorics and realities. Using a theoretical frame inspired by the Evolutionary Governance Theory, we identify mechanisms of reinterpretation and delimitation of participation in the context of evolving rural governance. Through a detailed case study of the Ethiopian agricultural extension system, we observed that various path dependencies, interdependencies, and goal dependencies in the extension system but notably also in the embedding system of rural governance limit and shape farmers’ participation. It is argued that the precise difference between official state rhetoric and on-the-ground realities of participation become understandable through reconstruction of embedding governance paths, and that the difference is further defined by relating it to the way other key concepts in rural development are implemented: decentralization, self-governance, and agricultural extension itself. Mapping out these coevolving rhetorics and realities gives insights in real reform options, for extension in particular and rural governance in general. Our case findings show that despite numerous reforms in the agricultural extension system and a steady increase in the extension coverage with a huge number of extension workers (Development Agents), participatory approaches largely failed to meet farmers’ needs.
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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 | 0.015 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.012 | 0.031 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| 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".