Between ‘the Technical’ and ‘the Social’? The Case of Farm Ponds for Supplemental Irrigation in Burkina Faso and Mali
Bibliographic record
Abstract
Adopting the perspective of practitioners, we analyse the case of farm ponds for supplemental irrigation built in Burkina Faso and Mali. We reflect on the ways in which climate technologies can contribute to smallholder farmers’ resilience to climate change, showing that in the different processes involved in the design and implementation of farm ponds as climate technologies, the distinction between infrastructure, equipment and machinery, on the one hand, and people, societies and communities, on the other, concealed the complexity of agricultural, agro-ecological and development practices. This ultimately hindered the potentially positive impacts of the technology and confirmed what the literature has already shown: that climate technologies should be approached as solutions that, regardless of their use of a particular piece of infrastructure or equipment, are always ‘socio-technical’.
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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 | 0.002 |
| Science and technology studies | 0.016 | 0.012 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".