How Technology Is Radically Reshaping Supply, Demand, and the Energy of Geopolitics
Bibliographic record
Abstract
Guest editorial To understand how radically the energy industry is changing, consider this: The United States is the number one producer of natural gas in the world. Given appropriate policy and smart investments, it could eventually attain energy independence. What is driving this energy revolution? Technology. Cutting-edge hardware and software are unlocking geological potential in places and ways hardly imaginable even a few years ago, and energy companies now rank among the most important—and sophisticated—technology pioneers in the world. Great Game 2.0 and the Power of One The global energy map has been redrawn and expanded by technology. Whereas the “Great Game”—the often violent scramble among nations for control of territories harboring energy reserves—is still relevant, today it has become equally, if not more, important to control the technology assets, the hardware, and the software. Thus, the game has changed. New technologies have empowered nations, and they have made corporations and individuals active participants in the energy game. Smart meters, the Internet, and advanced software allow individuals to fine-tune energy consumption, underscoring the “Power of One”—the ability of every person to proactively manage his or her energy consumption and carbon footprint. This generational change is a function of heightened awareness of the impact of energy consumption on household expenses, foreign policy, and the environment. Energy consumption is no longer an economic act; it is becoming a conscious act and an act of conscience. By understanding and managing energy use, individuals can save money, companies can increase profits, and both can lessen their environmental impact. Everyone wins. Danger Ahead—A License to Operate? The breakneck pace of the energy technology revolution has likely masked inherent risks, especially in terms of the environment and public reaction. The expansion of hydraulic fracturing and the accelerated production of the Canadian oil sands coincided with the global economic crisis that began in 2008. This initially blunted reaction to potential dangers of new energy technologies, because the general public was absorbed by its core economic concerns and thus inclined to think more about the savings from less expensive energy than about environmental concerns. Essentially, in the competition between desire for cheaper energy and fear of the eco-consequences of fossil fuels, desire was at the forefront. Today, environmental concerns are again front and center because of the recent series of energy-linked environmental challenges and public concerns: the Gulf of Mexico oil spill, the Fukushima nuclear incident, the controversy over hydraulic fracturing, and more. The unsettled nature of these concerns means companies still have not secured a free and clear “license to operate” from the public. Our knowledge of the potential and consequences of new technologies is in its infancy. “The Great Game 2.0” may well decide which countries and companies emerge as enduring powers in the 21st century.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".