A utilização de recursos energéticos restritos e não restritos: implicações econômicas e análise empírica da organização para cooperação e desenvolvimento econômico.
Bibliographic record
Abstract
In the present world development scenario the concern about energy sources to be used by each country has become of paramount importance due to the relationship between energy use and progress of each country. In this sense, it is necessary to analyze what type of energy investment will be targeted by each country. Thus, this study aims to analyze the efficiency, from an economic point of view, energy production from non restricted sources and restricted in OECD countries and their key partners, with the temporal cut year 1973 to 2012. To carry out this analysis is considered the model of optimal economic growth presented in Oliveira (2010) establishing the existence of a relationship between the marginal productivity of restricted and unrestricted energies, so that what will define which of the two the more efficient is the ratio between the marginal productivity of the unrestricted and restricted energy multiplied by the inverse weighting function restricted resource extraction. Finally, we performed empirical analysis of this result for the target countries of study, where it has the result that it is more efficient to use energy from not restricted sources in South Africa, Germany, Austria, Brazil, Canada, Chile, Denmark , Spain, Finland, Greece, Indonesia, India, Ireland, Japan, Mexico, Norway, Portugal, Sweden and the UK, as was more efficient use of energy from sources restricted in Peru, as well as verification that the case the other countries to make the decision on what type of energy is to invest, you need to be aware of the value of the restricted resource extraction weighting function.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".