Fueling Up: The Economic Implications of America's Oil and Gas Boom
Bibliographic record
Abstract
With a changing energy landscape, energy is once again at the forefront of the global policy debate, echoing the oil crisis of the 1970s. But both the global energy market and its role in the global economy have changed considerably over the past three decades, and the energy policies and institutions developed during the last crisis are not well suited to address our current energy security challenges. The centre of global energy demand is rapidly moving East, thanks to the rise of China and other Asian economies. And after years on the periphery, the centre of global energy supply is beginning to move back West, due in large part to the development of unconventional oil and gas resources in Canada, the United States, and Latin America. The Middle East and North Africa are as much a source of energy supply instability today as they were in the late 1970s, although for different reasons. And it's no longer just oil and gas that are driving global energy security concerns--coal and rare earth minerals are receiving increasing attention. Finally, the financialization of energy commodities has introduced new market function and security concerns. While each of these trends has been analysed individually, there does not yet exist an assessment of their collective implications for national security, international institutions, and the global economy. Trevor Houser and Shashank Mohan masterfully paint a comprehensive picture of this complicated mosaic and offer a way forward.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".