Energy Solutions, Neo-Liberalism, and Social Diversity in Toronto, Canada
Bibliographic record
Abstract
In response to the dominance of green capitalist discourses in Canada's environmental movement, in this paper, we argue that strategies to improve energy policy must also provide mechanisms to address social conflicts and social disparities. Environmental justice is proposed as an alternative to mainstream environmentalism, one that seeks to address systemic social and spatial exclusion encountered by many racialized immigrants in Toronto as a result of neo-liberal and green capitalist municipal policy and that seeks to position marginalized communities as valued contributors to energy solutions. We examine Toronto-based municipal state initiatives aimed at reducing energy use while concurrently stimulating growth (specifically, green economy/green jobs and 'smart growth'). By treating these as instruments of green capitalism, we illustrate the utility of environmental justice applied to energy-related problems and as a means to analyze stakeholders' positions in the context of neo-liberalism and green capitalism, and as opening possibilities for resistance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".