Climate Discourse Among Canadian NGOs: Ecological Modernization, Civic Environmentalism, and Climate Justice
Bibliographic record
Abstract
This research examines the websites of twenty-three Canadian NGOs using critical discourse analysis to understand: (i) What climate change discourses are dominant among Canadian NGOs? (ii) What are the goals and strategies being promoted through these discourses? (iii) How are climate issues being framed by these organizations? (iv) Who do NGOs see as the primary agents and mechanisms of change in addressing climate change? The findings illustrate three main discourses--ecological modernization, civic environmentalism, and climate justice--though the distinctions between discursive categories are often blurred as many organizations draw from multiple discursive narratives in their appeals for climate action. Ecological modernization discourse underpins much of the framing of climate change as a threat to the Canadian economy and the benefits of transitioning to a zero-carbon economy through market interventions and green innovation. Equally represented is a Canadian stream of civic environmentalist discourse. Civic environmentalism has a strong presence in how many NGOs attribute the climate crisis to an imbalance in decision-making power between elites and the rest of Canada where the solution is then to restore democracy in political institutions. Climate justice was least represented but offers a more critical understanding of the nature of the climate crisis and emphasizes the need for a broad-based movement that unifies the fights for social, economic, and ecological justice.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.047 | 0.022 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 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".