Bibliographic record
Abstract
The global energy scenario has transformed in the past 20 years. Oil demand, earlier driven by the West, is now shifting to the East, more specifically to Asia. New oil supplies from North America have challenged the hegemony of the traditional oil exporters from West Asia and Africa. India, once a marginal player in the world oil market, is now a valued customer providing demand security for oil exporters. This book systematically examines India’s oil and gas trade, which makes it the world’s third largest importer of oil after China and the US. It explores the changing patterns of oil demand and supply, and the growing market for natural gas, renewable energy, biofuel, and alternative sources of energy. Further, the volume discusses a range of issues that affect India’s position in the global energy econom,y such as The geographic shifts in energy production and trade; international relations and economic sanctions that affect the oil trade; India’s quest for energy security; and contest with China for oil assets; Building new partnerships, and investing in stable, oil-rich countries like the US and Canada, while keeping up existing energy relations with Saudi Arabia, the UAE and Kuwait; Using market mechanisms to ensure energy security. Topical and comprehensive, this book in The Gateway House Guide to India in the 2020s series will be useful for scholars and researchers of international relations, geopolitics, foreign policy, security and strategic studies, energy studies, West Asia studies, South Asian studies, and international trade. It will also be of interest to policymakers, diplomats, career bureaucrats, and professionals working with think tanks, academia and multilateral agencies, media agencies, and businesses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".