Bibliographic record
Abstract
Eau Canada analyzes aspects of contemporary water management and governance practices in Canada, including decision-making procedures; business models; legal and jurisdictional frameworks; political cultures; water rights regimes; and questions of participation, transparency, and accountability in water management.Many other equally important areas of water management and academic inquiry -such as aquatic science and engineering -are excluded or dealt with only in passing.Any analysis is an exercise in the drawing of boundaries, and the boundaries for some subjects -particularly environment-related issues -are more porous and artificial than others.Most experts working on water issuesincluding the majority of contributors to this book -would likely agree that an integrated approach, although difficult, is absolutely necessary, given that water is a multi-purpose resource that is essential for life, transcending jurisdictional and geopolitical boundaries and linking complex social and technical systems.The relatively narrow focus on water governance and management is justified insofar as many Canadian water experts feel that water governance in Canada is in a state of crisis (in the true sense of the word): a turning point in which weaknesses are exposed, challenges are confronted, and opportunities for innovation arise."Crisis" is an over-used and tired term, but it is appropriate here for two reasons: (1) the potentially dramatic consequences of the systemic weaknesses in contemporary Canadian water governance, and (2) the opportunity that this offers for innovation and renewal in our relationship to water.This, in turn, lent impetus to the decision to target this book at a general audience rather than at specialists.Reflecting the diversity of stakeholders in Canadian water debates, contributors to this book have been drawn from xvi universities, think tanks, NGOs, and government.They have written chapters aimed at a similarly diverse audience in the hope that Eau Canada will serve to spark debate about the nature, causes of, and solutions to persistent problems in our relationship with water.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.488 | 0.250 |
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".