Indigenous Water Co-Governance: Emerging Models of Distributed Water Governance in British Columbia and Alberta
Bibliographic record
Abstract
The emphasis on Indigenous law is of pressing importance given that evolving legal \nframeworks have created expanded approaches to Indigenous title, rights, and traditional \nterritories and hence expanded roles for Indigenous peoples in resource governance. This \ncreates a challenge for all levels of government (including Indigenous governments), as new \nmodels of governance (and stakeholder relationships) are being debated and indeed \ncreated. \nThis challenge has inter-related economic, policy and governance dimensions. Indigenous \ncommunities in Canada are currently grappling with a range of water-related issues, \nincluding access to safe drinking water, environmental water quality, and associated health \nand livelihoods issues. In some regions, particularly Western and Northern Canada, these \nissues are exacerbated by development pressures associated with resource extraction (e.g. \noil and gas development, forestry, hydro-electricity). In this context, there are number of \nchallenges that stem from legal and regulatory frameworks, including inadequate \nconsultation, lack of community capacity to participate in engagement and consultation \nprocesses, insufficient transparency, and outdated regulations (e.g. with respect to new \npollutants) and perceived regulatory capture. \nIn the absence of effective responses to these challenges, there are a number of potential \nconsequences, including expensive and protracted litigation, higher appeals to (and thus \nincreased caseloads for) regulatory oversight bodies, and political mobilization and protest.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".