Bibliographic record
Abstract
Water is integral to Alberta’s economy, grounded in agriculture, power generation, extractive industry, tourism, and recreation. In 2003, the Government of Alberta released the Water for Life Strategy (the Strategy) amidst growing public concerns over multiple impacts on provincial water resources. The Strategy is a framework document guiding the development of watershed plans across the provincial landscape to be implemented by Watershed Protection and Advisory Committees (WPACs). This paper explores the extent to which First Nations in Alberta were included in the government’s development of the Strategy and in the implementation of the Strategy by the WPACs. Our research data was gathered through key informant interviews with WPAC personnel as well as content analysis of relevant planning documents from provincial and WPAC sources. The research results point to an absence of First Nations inclusion in both the development of the provincial water Strategy as well as the implementation of the Strategy through the WPAC policies and plans. The results also identify institutional gaps and opportunities by which the provincial government and the WPACs may engage more effectively and inclusively with Indigenous communities. From our analysis, we recommend a series of institutional arrangements to advance far greater inclusion of Indigenous voices and recognition of Indigenous peoples as rights-holders, in watershed planning in Alberta.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.015 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".