Changes in institutional and social–ecological system robustness due to the adoption of large‐scale irrigation technology in <scp>Navarre (Spain)</scp>
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Many regional and national organisations promote the modernisation of agriculture by supporting new technologies to increase their territory's competitiveness in a free‐market context. Such technologies and their associated intensive land management practices are geared towards obtaining higher yields. However, their application also entails changes in water and land management institutions, which could alter interactions among multiple components of the agrarian social–ecological system and potentially weaken the system. Here, we assess how these components and their relations change in a village situated in Navarre (Spain) after the uptake of large‐scale irrigation infrastructure. Specifically, we analyse such changes by comparing how the design principles for robust social–ecological systems manifest before and after the adoption of large‐scale irrigation. Our findings indicate that an unequal distribution of water and land induces some farmers to abandon their agrarian activities. Our case study also shows how irrigation communities have partially lost their autonomy to self‐organise and make agrarian management‐related decisions. We suggest that the adoption of large‐scale irrigation in this region contributes to a decrease in cooperation among resource users, and between users and infrastructure providers. This is due to a decline in the capacity to achieve collective‐choice arrangements and higher external control and monitoring of water use. We argue that the current agrarian management changes may damage social–ecological system robustness and affect the sustainable use of common‐pool resources, leading farmers to maladaptation to climate and market variability.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it