Political movement: The role of grassroots activism on the development of wastewater treatment policy in Victoria, Canada
Bibliographic record
Abstract
The City of Victoria has been discharging untreated sewage into the Pacific Ocean since 1894 (CRD 2017b; Kines 2020; Meissner 2021). On December 15th, 2020, this practice stopped after the opening of the $775 million McLoughlin Point Wastewater Treatment Plant, which now serves the City of Victoria, 13 municipalities, and six First Nations (CRD 2017b; Kines 2020). The process of deciding whether, where, and how to build the plant was the result of decades of intense political debate and the work of dedicated activism, with groups advocating passionately for a diverse set of outcomes. \n \nThis thesis conducted semi-structured interviews with local activists, non-governmental organization (NGO) actors, politicians, and bureaucrats to address the research question, How did the actions of grassroots activists in Victoria, Canada between 1990 and 2020 affect the decision-making and planning process regarding the Mcloughlin Point Wastewater Treatment Plant? To address this question, a thematic analysis was conducted, resulting in three themes, which are further contextualized using an analytical framework describing the different forms of power available to actors in a political system. \n \nIt was found that activists utilize discursive power, or the power to shape ideas through communication. In this case study, activists primarily accomplished this in two ways: through harnessing scientific evidence, and by appealing to emotions. Additionally, activists can achieve direct power over the policymaking process by running for office and becoming elected representatives. Grassroots activism is considered by some to be one of the most efficient ways of encouraging pro-environmental actions (Alisat & Riemer, 2015). This thesis contributes to the understanding of the actions that activists can take in their work and their potential effectiveness, which can allow activists to make more informed decisions on how to allocate their limited resources to have the highest possible impact.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.026 | 0.011 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".