Natural resource industry involvement in collaboration for water governance: influence on processes and outcomes in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Natural resource industries are increasingly significant actors in environmental decision-making. Possessing vast institutional and technical capacity, firms have an important role to play in ‘new’ governance strategies such as collaboration. These strategies are often based upon assumptions of equitable influence. This paper investigates the nature of resource industry participation in collaborative water governance in Canada, and the potential consequences of that participation as investigated using power theory. The study used comparative cases to reveal that resource industries are able to shape collaboration, and the issues collaborated upon, at multiple analytical levels both internal and external to the collaborative process in ways not available to other actors. Analysis also revealed that resource industry participation in collaboration did not reflect a commitment to engage in shared learning and the reexamination of values and interests as presupposed by collaborative theory. Collaboration is thus challenged in producing equitable, representative outcomes when resource industries participate.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it