Sustainability-Based Framework Development and Specification for Coal Phase-out Policy: Just Transition and Sustainability Requirements in the Canadian Context
Bibliographic record
Abstract
Following the Paris Agreement and the commitment to the NDCs (Nationally Determined Contributions) by its members, Canada has reinforced the engagement with a decrease of fossil fuel consumption through a federal policy to phase-out coal by 2030. This thesis analyzes the necessary sustainability criteria reliant on socio-ecological and economic aspects to assess national coal phase-out policy with particular attention to the Canadian case. \nThe research discusses the specification of essential sustainability-based criteria for national coal phase-out policy with just transition and sustainability requirements and integrates other specific sustainability criteria, illuminated by the Canadian case study. The proposed sustainability framework for coal phase-out policy instruments brings to light the necessity of an integrative approach, embedding essential issues for sustainable national climate change policy such as equity and just transition principles in alliance with environmental requirements. This research identifies the benefits of an integrative and robust sustainability framework to promote environmental progress and equity for transition processes to a low carbon economy. \nThis thesis work aims to answer three central research questions: Firstly, what specific requirements are needed to ensure a coal phase-out policy is aligned with contributions to sustainability, with particular attention to climate change mitigation and just transition? Secondly, what can be learned from coal phase-out experiences already implemented globally in terms of strategies and tools applied, challenges, barriers, and drivers for coal phase-out? Thirdly, how can the characteristics of the Canadian design and implementation of coal phase-out policy inform the development and specification of a sustainability-based framework for informing national coal phase-out policies? \nTo address these questions, the thesis builds on Gibson et al.'s (2005) sustainability assessment framework and adapts it to coal phase-out policies. The resulting framework comprises five key categories: socio-ecological system integrity and compliance with fundamental climate change mitigation objectives, livelihood sufficiency, affordability, equity, and opportunity, social dialogue, participatory decision-making, and democratic governance, Adaptability, precaution, and monitoring for long-term sustainability, and Governance accountability, inter-jurisdictional collaboration, and government support. \nThe framework is tested through application to the Canadian case study, which not only validates and enhances its criteria but also provides context-specific insights. The study emphasizes multi-level governance, inclusive engagement, transition fuel challenges, community vulnerability, and establishment of governance bodies as crucial aspects in coal phase-out policy. \nIn conclusion, this research contributes a holistic sustainability-based framework for assessing and guiding coal phase-out policies. Its application to the Canadian case underscores its practical value while acknowledging the need for context-specific adaptation. By promoting an integrated approach that encompasses social, economic, and environmental dimensions, the framework offers a pathway towards sustainable and equitable coal phase-out, essential for a low carbon future.
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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 | 0.023 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.011 | 0.012 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".