Bibliographic record
Abstract
After the two oil shocks of the 1970s when OPEC was able to strongly increase the prices at the expense of economic recessions, a collapse followed in 1986, the so called oil counter-shock, due to the disagreements within OPEC and the decisions taken by Saudi Arabia to strongly increase oil supply. After that the prices fluctuated under $ 50/barrel and the periods of declining prices were more numerous than those of the boom, but each boom created the conditions for a subsequent fall in prices. The oil’s price volatility has increased dramatically in the last two decades, and in late 2016 a larger alliance/group OPEC+ was formed between OPEC and some non OPEC countries (13). OPEC + is an alliance of 13 OPEC members and 13 non-OPEC members, which together control over 50% of the world's crude oil supply and hold about 90% of certain oil reserves. OPEC+ alliance, based on close cooperation between Saudi Arabia and Russia, was able to reach an agreement in April 2020 and to cut oil supply by 10 million barrels/day and to extend the agreement in 2020 and in 2021, to stabilize the market and increase the prices, also with the support of other producers, such as the USA, Canada, but mainly due to the recovery of consumer demand in developed countries. In view of all those mentioned evolution my article aims to assess OPEC+ role in assuring the stability of oil prices while maintaining a balanced growth for the total global production.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".