Understanding human adaptation to drought: agent-based agricultural water demand modeling in the Bow River Basin, Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The farmers in the Bow River Basin (BRB), Canada, have adopted water conservation strategies to reduce water needs. This reduction, however, encouraged the expansion of irrigation, which may rebound agricultural water demands. This paradox requires an understanding of human adaptation to drought by mapping individual farmers’ water conservation decisions to the dynamics of the basin-wide water demand. We develop an agent-based agricultural water demand (ABAD) model, simulating farmers’ behavior in adopting new on-farm irrigation systems and/or changing crop patterns in response to drought conditions in the BRB. ABAD demonstrates (1) how farmers’ attitude toward profits, risk aversion, environmental protection, social interaction, and irrigation expansion explains the dynamics of the water demand and (2) how the conservation program may paradoxically lead to the rebound phenomenon. ABAD, subject to its conceptualization limitations, can be used for exploration and scenario analysis of future agricultural water demand in response to water conservation programs in the BRB.
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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