Conflict, Constituent Power and Institutional Legitimacy in the Canadian Oil Sands
Bibliographic record
Abstract
Much has been written about the loss of trust and issues concerning ‘social license to operate’ (SLO) in relation to the Canadian oil sands, raising questions about whether there is a crisis of legitimacy. This article considers the implications of constituent power and the democratic constitutional theory advanced by Colón-Ríos for the legitimacy of modern oil sands institutions. Building upon Colón-Ríos’s theory, this article proposes the examination of constituent power as an analytical approach to understanding institutional legitimacy in resource conflicts where legitimacy is contested. In other words, where the exercise of constituted power raises questions of legitimacy, this ought to trigger an examination of the democratic legitimacy of the overarching constitutional regime by reference to constituent power. If there is a democratic deficit in the formation of the constitutional regime that empowers them, it may be difficult to defend the regulatory bodies responsible for administering the oil sands as normatively legitimate. This article does not aim to draw broad conclusions about the legitimacy of oil sands governance institutions or the Canadian constitutional regime per se. Rather, it sees the contested nature of legitimacy as a potential indicator that difficulties in resolving oil sands conflicts may stem from the existence of deeper systemic issues relating to the constitutional regime in which the institutional framework is embedded. Focusing on constituent power theory to examine the democratic legitimacy of the overarching constitutional regime may serve an explanatory role, perhaps shedding light on why democratic approaches are not reflected in oil sands decision-making. It might also further clarify why popular acceptance of the system of governance remains in question, particularly by some Aboriginal communities, and why public stakeholders have struggled with having their concerns addressed appropriately. Such an examination may reveal the true extent of the democratic deficit and, therefore, provide a deeper understanding of the legitimacy issues that oil sands institutions might face when determining ways to improve governance, particularly where there are demands for more deliberative, democratic decision-making. This analytical approach may also potentially be valuable in institutional contexts other than oil sands and resource governance.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.022 | 0.038 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".