Constructing the Public Sphere in Compromised Settings: Environmental Governance in the Alberta Forest Sector
Bibliographic record
Abstract
À une époque où l'enthousiasme se manifeste pour une gouvernance environnementale plus délibérative et participative, des études critiques sur ces activités s'avèrent grandement nécessaires. Un forum très en vue sur la gouvernance, le Comité de consultation publique, en est venu à jouer un rôle d'une importance capitale dans la réglementation législative et axée sur les forces du marché des ressources forestières. L'article présente une évaluation critique de ces milieux environnants de plus en plus privés et localisés pour le discours politique du secteur forestier de l'Alberta. Quoique la prudence soit conseillée concernant le potentiel d'engagement actif du citoyen à l'intérieur de comités financés par les entreprises, l'étude de cas révèle l'importance de la variation contextuelle sur la qualité de la délibération. At a time when enthusiasm waxes for a more deliberative and participatory environmental governance, critical inquiries into these activities are sorely needed. One prominent governance forum is the public advisory committee, which has come to play a central role in the legislative and market‐based regulation of forest resources. This paper offers a critical assessment of these increasingly privatized and localized settings for political discourse within the forest sector of Alberta. Although caution is urged regarding the potential for active citizen engagement within corporate‐sponsored committees, the case study reveals the importance of contextual variation in the quality of deliberation.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.045 |
| Scholarly communication | 0.022 | 0.006 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".