Explaining Divergent Energy Paths: Electricity Policy in Argentina and Uruguay
Bibliographic record
Abstract
South America is a region that has received little attention in the literature dealing with renewable energy policy politics. Yet, it is a region in dramatic transition and this makes it an important case for examination. In this dissertation, Argentina and Uruguay, two countries that are experiencing rapid socioeconomic and electricity transition, are compared in relation to their energy policies related to electricity supply. The aim of this study is to compare the similarities and differences of energy policies in the two countries¬––from two selected electricity systems––explaining why and how certain policy ideas, understandings or beliefs (but not others) were adopted in their energy policies. This comparative case study of the historical policy process of energy policy seeks to understand why the countries showed different commitments to different forms of energy and how the development of renewable energy in particular can be explained in each case, all the while trying to identify supportive and hindering factors. Additionally, attention is given to the evolution of the German and French nuclear and/or renewable energy policies as they provide good examples in relation to their different energy choices. While Germany––together with Spain, Denmark, and California––is considered one of the worldwide pioneers in the deployment of wind and renewable energy, France––together with Canada, Japan, Sweden, and US––is deemed to be a reference in nuclear energy. This dissertation examines what can be learned from these two countries and whether there are elements that might be interesting to apply in Argentina and Uruguay for a better understanding of the policy process in these two countries. Both Argentina and Uruguay have faced energy supply shortages since the mid 2000s. Yet, while Argentina decided to focus more on increasing nuclear power and start developing some renewable energy, Uruguay rejected nuclear power and decided to begin significant development of renewable energy. The paradox is that having one of the most important domestic wind industries of South America, outstanding renewable resources and previous regulation in the sector, Argentina did not consider deploying renewable energy as a significant source to solve their electricity shortage. In contrast, Uruguay, which must import all components for their wind turbines and had no previous policies promoting renewable energy, saw in the development of renewable energy a good alternative to diversify their electricity mix and solve their electricity scarcity problem. The comparison of similarities and differences entails both why and how questions. The answer to the first question explains why facing a similar electricity supply shortage since the mid 2000s, Argentina and Uruguay decided to set different renewable energy and nuclear power goals in their public agendas. The how question describes the (policy) process behind the development of renewable and nuclear energy and the way key actors related to these options.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".