Socio-hydrology and the science-policy interface: a case study of the Saskatchewan River Basin
Bibliographic record
Abstract
Abstract. While there is popular perception that Canada is a water-rich country, the Saskatchewan River Basin (SRB) in Western Canada exemplifies the multiple threats to water security seen worldwide. It is Canada's major food-producing region and home to globally-significant natural resource development. The SRB faces current water challenges stemming from: (1) a series of extreme events, including major flood and drought events, since the turn of the 21st century, (2) full allocation of existing water resources in parts of the Basin, (3) rapid population growth and economic development, (4) increasing pollution, and (5) fragmented governance that includes the Provinces of Alberta, Saskatchewan, and Manitoba, various Federal and First Nations responsibilities, and international boundaries. The interplay of these factors has increased competition for increasingly scarce water resources across economic sectors and among provinces, between upstream and downstream users, between environmental flows and human needs, and among people who hold different values about the meaning, ownership, and use of water. These current challenges are set in a context of significant environmental and societal change, including widespread land modification, climate warming, and deep uncertainties about future water supplies. We outline the geographic setting of the SRB and its environmental history, and then discuss the major challenges to water security from: (1) environmental change, (2) rapid growth and economic development, and most importantly, (3) a governance model unsuited to managing complex and uncertain water systems. We conclude with a discussion of the emerging field of socio-hydrology and what it can contribute to knowledge translation, water management, policy, and governance in the SRB and worldwide.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".