Broadening democracy against environmental justice: The example of Montreal borough councils
Bibliographic record
Abstract
In this reflection, through observation of citizen participation in several local Montreal municipal councils, I examine whether and how people discuss environmental issues. More specifically, I seek to determine whether the politicization of environmental issues favours the expression of environmental justice. I use this term to refer to the social dimension of environmental questions, given that people of different social classes or identities are not affected by environmental issues in the same way. Does the politicization of environmental issues reproduce an unjust social order or does it encourage the struggle against inequalities? The answer reached here underlines the predominance of politicization through the challenging of democratic processes rather than a substantive politicization (where citizens debate the content of issues and discuss values or identities), which hinders the emergence of environmental justice. This study makes two contributions. First, it points out that, beyond conflict, addressing the avenues that conflict takes is vital. Second, while most analyses consider environmental justice within civil society organizations and on the “margins”, this reflection tackles environmental justice within institutions themselves, namely the favoured places of production of social norms. Apprehending the role of institutions in the politicization of environmental issues is, thus, crucial to highlighting some aspects of social framing and the place of environmental issues in society.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.032 | 0.018 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".