The role of non-governmental organizations in the articulation and enhancement of participatory rights in environmental decision-making as evidenced in the process leading up to and after MiningWatch Canada v. Canada (Fisheries and Oceans), 2010 SCC 2
Bibliographic record
Abstract
This thesis used case study research methods to examine the role played by Non-Governmental Organizations (NGOs) and the methods they use to increase public participation in environmental matters. It does this by investigating the process leading up to and following a Supreme Court of Canada (SCC) decision, that of MiningWatch Canada v. Canada (Fisheries and Oceans) (2010 SCC 2). Specifically, the strategies and methods used by NGOs in this study and their impact on public participation during and in the aftermath of the decision are examined. The primary research question is: what is the impact of NGOs on participatory politics as seen in the SCC decision, MiningWatch Canada v. Canada? Other research questions examined are: what role have NGOs had in increasing participation in environmental decision-making, and: how do NGOs increase public participation in environmental decision-making? Three main groups of strategies are used by the NGOs: “Legal”, “Challenge or Inform Government”, and “Creating an Emotional Response in an Audience.” Strategies common to all NGOs in this study were: “Increase Knowledge” by “Networking,” “Working with Communities at a Grass Roots Level” and “Publications and Reports”. The argument this thesis presents is that democracy is a dynamic process and various strategies can be used to influence participation in environmental decision-making. Specifically, groups of citizens can form in response to an issue, raise public awareness and encourage legislation and policy changes in the search for social progress; in this case, increase public participation in matters involving the environment.
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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 | 0.035 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.040 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".