The Electric Matrix of the State of São Paulo Toward the Just Energy Transition: Comparative Analysis of Strategies Based on the Experience of the 2014–2015 and 2021 Water Crises
Bibliographic record
Abstract
This paper analyses the evolution of the electric matrix of the Brazilian state of São Paulo between 2012 and 2022, assessing the impacts on the electric system of two major water crisis events that occurred in 2014–2015 and 2021. We conducted our analysis through the lens of just energy transition, which is here understood as an approach that encompasses elements from environmental, climatic, and energy justice in the study of energy planning and policies. In this sense, in this paper we focus on elements of distributive energy justice. We find that the electric matrix of the state had a slight but still insufficient diversification, remaining tied to a dependence on hydraulic and fossil fuel generation and highly vulnerable to water crisis events. In addition, we show how both water-crisis events significantly influenced electric generation in the state, leading to increases in costs and tariffs, which are implied in issues of distributive justice. From these results we conclude that, through the perspective of just energy transition, the energy planning of the state lacked a clear path to decarbonization and diversification, perpetuating a weakness that produces issues of energy justice in crisis scenarios.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".