Review of <i>Eau Canada: The Future of Canada's Water</i>. Edited by Karen Bakker.
Bibliographic record
Abstract
Karen Bakker has assembled an impressive list of contributors from academia and civil society, including internationally renowned physical and social scientists and prominent former civil servants. Lavishly referenced and weighing in at a hefty 400-plus pages, the book is broken into five main sections on current governance systems, jurisdictional fragmentation, privatization and markets, pathways to better management, and worldviews. Despite its heft, Eau Canada is a compelling read. A key message repeated in several chapters is that the federal government has largely ignored the principles set out in its own 1987 Federal Water Policy, which declared an overall objective of encouraging "the use of freshwater in an efficient, and equitable manner consistent with the social, economic, and environmental needs of present generations." A related point-though not commented on by any of the volume's contributors-is that the federal government has also failed to meet its international commitment to develop national Integrated Water Resources Management (IWRM) policies, made at the Johannesburg World Summit on Sustainable Development in 2002.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.013 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.007 |
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".