Assessing the Net Zero Measures and the Achievement of Just Outcomes in Community Energy and Emissions Planning in Canada: A Study of Three Communities in New Brunswick
Bibliographic record
Abstract
In response to the global mission of limiting warming to 1.5°C, numerous measures have been implemented throughout the world at different scales, specifically targeting the achievement of net-zero emissions by 2050. While these measures are designed to address issues related to climate change, they also create new adverse impacts and injustices in society. The concept of “just transition" emphasises the need to mitigate such impacts, paving the way towards creating more sustainable net zero communities. Community energy and emissions planning is one such measure that has gained widespread recognition internationally and in Canada which is aimed at taking climate actions in the local context to reduce emissions and overcome injustice that could emerge from the transition. New Brunswick (NB) communities are actively engaged in developing Community Energy and Emissions Plans (CEEPs) to both reduce emissions and enhance community resilience. Despite these efforts, challenges such as unclear guidance and vague conceptualizations of the concepts of net-zero emissions and just transitions still persist. These issues challenge the development of robust net-zero measures that also generate just outcomes and hinder the effectiveness of achieving their intended targets. Additionally, despite the widespread implementation of community energy and emissions planning in Canada, their academic application remains limited. To close these gaps, the current research focused on identifying the key indicators that would define what needs to be considered in the measures to reach net zero emissions and guarantee a just transition and reviewing the actions of developed CEEPs in NB from an emission reduction and a just transition-based perspective to understand the level of integration of the key considerations and to gain a better understanding of the actions that NB communities have planned to pursue in reaching their net zero targets. A literature review was conducted to identify key indicators for the concepts of net zero emissions and just transition. CEEPs of three communities in NB: the city of Fredericton, the city of Moncton, and the town of St. Andrews were analysed using qualitative data analysis i methods. The review of the literature generated 10 indicators that should be considered in the measures to achieve net-zero emissions and generate just outcomes. The case study analysis revealed that the integration of actions that would support the generation of just outcomes was significantly less than the measures for net zero emissions in the CEEPs of NB communities. And most of the actions that were identified for just transition indirectly support the indicators rather than directly addressing it.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.019 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".