ON‐FARM WATER CONSERVATION PRACTICES IN SOUTHERN ALBERTA<sup>1</sup>
Bibliographic record
Abstract
ABSTRACT: In southern Alberta, as elsewhere, pressures on limited water supplies are increasing. Not surprisingly, a great deal of attention has been focused on irrigated agriculture, which accounts for the largest share of water consumed in the region. In order to meet broadly accepted water conservation goals, some commentators have suggested that irrigation water use should be metered and that irrigators should be charged based on the amount of water used. An alternative proposal would have water management authorities rely upon the perceived adaptability of irrigators. This paper offers a perspective on the willingness of irrigators to conserve water. Based on a survey of 183 irrigation farmers conducted over the summer and early fall of 1998, we found that irrigators are generally aware of the need to conserve water and soil moisture, and that a variety of water conserving strategies were being employed. Water saving technologies specific to irrigation agriculture were less widely adopted. The findings suggest that there is considerable potential to reduce the amount of water consumed by the irrigation sector through increased efficiency, but that change will be limited if current economic circumstances and institutional arrangements persist.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".