Russian geopolitical objectives in the current oil price crisis, and implications for Canada
Bibliographic record
Abstract
Following the end of unsuccessful negotiations in March 2020 at OPEC headquarters in Vienna regarding oil production cuts, in the early March in Vienna (headquarters of OPEC), Russia and Saudi Arabia de-facto launched a prise war that resulted in a significant drop in oil prices (just as the COVID pandemic caused a concomitant drop in demand for oil), which in turn led to earthquake on the global oil market. As a result, prices of oil that plays an essential role for economies of both countries have plummeted to record lows no seen in two decades. While suffering economic losses, both countries, nevertheless, maintain an assertive posture and seem willing to pursue this policy even further. This paper examines the geopolitical logic of the Russian side – a country that has been placed under western economic sanctions since 2014 as a result of its illegal annexation of Crimea and destabilizing steps via proxy forces in the Southeastern Ukraine – and consequences thereof, particularly for Canada, as the price of Western Canada Select reached historic lows amidst a COVID-19 induced economic contraction.
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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 | 0.001 | 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 | 0.012 | 0.005 |
| Scholarly communication | 0.008 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".