Bibliographic record
Abstract
Winner of the Political Geography Specialty Group's 2015 Julian Minghi Distinguished Book Award! With almost the entire world’s water basins crossing political borders of some kind, understanding how to cooperate with one’s neighbor is of global relevance. For Indigenous communities, whose traditional homelands may predate and challenge the current borders, and whose relationship to water sources are linked to the protection of traditional lifeways (or ‘ways of life’), transboundary water governance is deeply political. This book explores the nuances of transboundary water governance through an in-depth examination of the Canada-US border, with an emphasis on the leadership of Indigenous actors (First Nations and Native Americans). The inclusion of this "third sovereign" in the discussion of Canada-U.S. relations provides an important avenue to challenge borders as fixed, both in terms of natural resource governance and citizenship, and highlights the role of non-state actors in charting new territory in water governance. The volume widens the conversation to provide a rich analysis of the cultural politics of transboundary water governance. In this context, the book explores the issue of what makes a good up-stream neighbor and analyzes the rescaling of transboundary water governance. Through narrative, the book explores how these governance mechanisms are linked to wider issues of environmental justice, decolonization, and self-determination. To highlight the changing patterns of water governance, it focuses on six case studies that grapple with transboundary water issues at different scales and with different constructions of border politics, from the Pacific coastline to the Great Lakes.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.031 | 0.012 |
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".