Water security in the Canadian Prairies: science and management challenges
Bibliographic record
Abstract
In this paper, we discuss the multiple dimensions of water security and define a set of thematic challenges for science, policy and governance, based around cross-scale dynamics, complexity and uncertainty. A case study of the Saskatchewan River basin (SRB) in western Canada is presented, which encompasses many of the water-security challenges faced worldwide. A science agenda is defined based on the development of the SRB as a large-scale observatory to develop the underpinning science and social science needed to improve our understanding of water futures under societal and environmental change. We argue that non-stationarity poses profound challenges for existing science and that new integration of the natural sciences, engineering and social sciences is needed to address decision making under deep uncertainty. We suggest that vulnerability analysis can be combined with scenario-based modelling to address issues of water security and that knowledge translation should be coupled with place-based modelling, adaptive governance and social learning to address the complexity uncertainty and scale dynamics of contemporary water problems.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.011 | 0.016 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".