Bibliographic record
Abstract
Energy-exporting countries have more at risk than any other participant in the world economy if the euro crisis plunges Europe into recession. These countries would likely experience greater losses in 2012 should Europe fail. Oil and natural gas prices would plummet, and the price collapse would likely be larger than the 2008–09 decline. Energy-exporting countries therefore should be working feverishly with the International Monetary Fund (IMF) and the European Union to rescue the euro. They, along with China and other large holders of foreign exchange reserves, should lend to the IMF to help it construct an emergency lending facility with capacity of more than €1 trillion. The fund, administered by the IMF, would be used to buy bonds issued by Greece, Italy, Spain, Portugal, and Ireland. The goal should be to bring interest rates on long-term bonds down to 3 percent. Simultaneously, efforts should be redoubled to fix the economic problems in the troubled nations and restore balance to their budgets. An energy price collapse would increase disruptions in energy-exporting countries, promote economic ills in some consuming nations, such as Canada, and almost certainly start yet a third, even more violent, economic cycle.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.051 | 0.006 |
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".