External imbalances pose a risk to global GDP
Bibliographic record
Abstract
Subject Global current account imbalances. Significance Global current account imbalances have declined but not disappeared since the 2008 global financial crisis. Some countries that previously had large deficits have switched to running surpluses, notably Spain, while former major surplus countries such as Canada now run deficits. The current account gap between the world’s two largest economies, the United States and China, has narrowed. At the same time, several countries have built up larger deficits or surpluses and aggregate external deficit and surplus positions have risen since 2014. Imbalances make the world economy more vulnerable to the shocks caused by the COVID-19 outbreak and oil market disruption at a time when trade and geopolitical tensions are already high. Impacts The United States, United Kingdom and Canada are large debtor nations but their role as issuers of reserve currencies protects them. India has the third-largest external deficit but its external debt is relatively small, although half is dollar-denominated and higher-risk. Corporate defaults were rising in China before the COVID-19 outbreak; further defaults, even relatively small ones, will hit supply chains.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.048 | 0.015 |
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".