Charting a Pathway for Water Security and Resilience
Bibliographic record
Abstract
The world is facing an escalating water crisis of quantity, quality, distribution, and allocation. Essential for life and a fundamental engine for economic growth, water is foundational to sustaining the world as we know it. Increasing frequency, magnitude, and extent of water-related natural and human-induced disasters including floods, loss of large freshwater lakes, and oil spills are not only threatening human wellbeing and economic growth, but social development and political stability even in high income countries. Patchwork remediation has failed; business as usual is no longer possible. Successfully addressing sustainable development challenges requires not only resources, but also massive behaviour changes that must occur at the level of governments, economies, and individuals. These changes require resilience on the part of all. We posit that resilience requires good growth, supportive governance, and community stewardship in order to be sustainable. This can be achieved and maintained through innovative engagement of the private sector in community investment strategies. The key lies in innovating technological and social change while aligning stewardship with the marketplace in order to foster awareness and behavioral change. Our solution plots a path towards sustainable water security and resilience through the Realising Action for Community Transformations (ReACT) implementation framework that is predicated on assessment, iterative learning, evidence-informed decision making, and an innovative approach to behaviour change - the PathSight Model. This private sector marketing model uses complex, big data sets combined with social sciences and technology to influence behaviour and impact outcomes. Integrating this model into the framework creates an innovative approach to sustainable water development and management through the use of science to inform and framing of causes that inspire, in order to engage the populace in necessary and sufficient behavioral transformations. Framework application is ongoing in the Lake Winnipeg Basin, Manitoba, Canada, where negative impacts on water resources appear to be occurring at ever increasing rates. Specific water-related threats to environmental, agricultural, political, and economic resilience in the province include floods and large scale eutrophication. Lake Winnipeg is threatened with ecosystem collapse and consecutive billion-dollar, one in 100 year floods have emptied provincial coffers and resulted in unpopular policy decisions that led to resignation of high level politicians and defeat of the longstanding government. Using an integrated PathSight framework the Lake Winnipeg problem is being reframed and re-distributed across a broader group of actors who may not have previously identified with either the problem or the solution(s). In this manner, politicians, private sector, and citizens are starting to articulate what they can do individually and together. In creating and mobilising a trans-sectoral, multi-stakeholder, multi-dimensional entity to bear on solving the Lake Winnipeg challenge, opportunities for shared governance, policy alignment, and grassroots action are emerging.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 teacher head, 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".