Climate Justice & Inequality: The Future of Canadian Climate Policy — with Marc Lee
Bibliographic record
Abstract
Co-Director of the Climate Justice Project at the Canadian Centre for Policy Alternatives, and senior economist, Marc Lee, joins Am Johal to discuss the successes and failures of Canadian climate policies across the political spectrum. Marc speaks about the origins of the Climate Justice Project, and conceptualizes how reaching a net-zero carbon economy can be achieved — through a fundamental restructuring of Canadian and BC systems, and the implementation of decolonizing practices.\n\nAm and Marc also discuss how approaches like carbon pricing and carbon capture systems do little to counteract climate change, and instead offer “escape hatches” for the fossil fuel industry. They explore how other government-based responses like subsidizing pipelines, or setting climate goals for the distant future, do not adequately address the imminent threat of climate change. Marc ends by discussing how we need to deal with this climate emergency with the same level of urgency that was enacted in BC’s COVID-19 response.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.026 | 0.007 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.023 | 0.002 |
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".