Water Policy, Imagination and Innovation: Interdisciplinary Approaches
Bibliographic record
Abstract
This book explores creative interdisciplinary and potentially transformative solutions to the current stalemate in contemporary water policy design. A more open policy conversation about water than exists at present is proposed - one that provides a space for the role of the imagination and is inclusive - of the arts and humanities, relevant stakeholders, including landholders and Indigenous peoples, as well as science, law and economics. Written for a wide audience, including practitioners and professional readers, as well as scholars and students, the book demonstrates the value of multiple disciplines, voices, perspectives, knowledges and different ways of relating to water. It provides a fresh and timely response to the urgent need for water policy that works to achieve sustainability, and may be better able to resolve complex environmental, social and cultural water issues. Utilising a broad range of evidentiary sources and case studies from Australia, New Zealand, Canada and elsewhere, the authors of this edited collection demonstrate how new ways of thinking and imagining water are not only possible but already practised, and growing in saliency and impact. The current dominance of narrower ways of conceptualising our relationship with water is critiqued, including market valuation and water privatisation, and more innovative alternatives are described, including those that recognise the importance of place-based stories and narratives, adopt traditional ecological knowledge and relational water appreciations, and apply cutting-edge behavioural and ecological systems science. The book highlights how innovative approaches drawing on a wide range of views may counter prevailing policy myopia, enable reflexive governance and transform water policy towards addressing water security questions and the broader challenges posed by the Anthropocene and the UN Sustainable Development Goals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.009 | 0.074 |
| Scholarly communication | 0.025 | 0.023 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".