SRI AND ENERGY TRANSFORMATION ON THE WAY TO SUSTAINABLE COMPETITIVENESS
Bibliographic record
Abstract
Russian war against Ukraine turns to challenge for the whole world. The full scope of consequences is difficult to assess now, but some of them have been already clear. As a result, the world economy is under exposures of inflation, disruptions on GDP growth, food and energy crises and further supply-chain pressures. Energy prices volatility adds uncertainty to the whole system of socio-economic relations. Energy turns to weapon against the world stability. The paper concentrates on the idea that current situation in the energy sector calls for a prompt reaction on challenges, including war consequences. That, in turn, requires sustainable and responsible investment (SRI) and financial innovations for immediately energy transformation, which is an essential element for sustainable competitiveness of countries. It is also crucial not to lose a track for net zero emissions by 2050. Such investment which combines financial goals with ecological, social and governance issues are covered by umbrella term “sustainable investment”. Sustainable investment became a strong trend on global financial market, which is popular with institutional and private investors. Investment in renewable energy is a part of SRI and countries’ sustainable competitiveness depends on the SRI volumes. The research is aimed at studying interconnection between SRI and energy transformation on the way to sustainable competitiveness. The processes on the global energy market are investigated and main weak points which are sources of risks for the world economy are defined. Three significant energy-related weak points turned into risks for the world are highlighted: the level of dependency from imported gas (for European countries dependency from Russian gas in particular); energy prices volatility; energy structure (nonrenewable vs renewable). It is generalized governmental approaches in the sphere of energy transformation driven by a combination of energy security concerns and climate ambitions. The paper contains an assumption about correlation between SRI and countries’ sustainable competitiveness. This hypothesis is confirmed using correlation analysis (biserial correlation) for five countries (Germany, the USA, Canada, Australia and Japan). Strong relationship between these variables is shown. This allows to make conclusions that increasing of SRI volumes in general and clean energy projects in particular, are predominant conditions for the sustainable competitiveness of country, which is oriented to the long-term prospective and based on effective usage of all available sources, including energy, fast transformation of energy systems to the renewable sources.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".