Corporate Consolidation in The U.S. Oil and Gas Sector: Implications for the Global Oil Market
Bibliographic record
Abstract
The U. S. oil and gas sector is experiencing a new wave of mergers and acquisitions. The world’s largest private vertically integrated oil and gas companies are adding the best assets from the tight oil and deepwater shelf sectors to their production portfolios. At the same time, the consolidation of so-called independent producers is taking place. The consolidation of U.S. oil companies will have a significant impact on the global oil market through several channels. First, the concentration of tight oil production in the hands of a small number of large companies will make it more resistant to price shocks, both to a decrease and an increase in oil prices. Second, the anticipated increase in oil prices will open up opportunities for OPEC countries in the second half of the current decade to increase oil production while simultaneously receiving sufficient revenue from its export to support the required budget expenditures. Third, the redistribution of the domestic oil market in the United States in favor of American oil companies will continue, as oil imports are reduced in favor of domestic production. Fourth, the concentration of American oil production in the hands of a limited number of companies will lead to an even greater increase in the export of crude oil and petroleum products from the United States. Fifth, the consolidation will push faster growth in oil production in the Western Hemisphere – the USA, Canada, Guyana and Brazil. Sixth, the consolidation of American oil companies will encourage scaling up of business by national state oil companies in OPEC countries.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".