Global value chains in the current trade slowdown
Bibliographic record
Abstract
Real growth in global trade has decelerated significantly since its sharp recovery in 2010. Year-on-year growth in global real trade decelerated from 13.3 percent at the end of the first quarter of 2010, to 9.9, 3.1, and 0.5 percent at the end of the first quarters of 2011, 2012, and 2013, respectively, while picking back up to 3.9 percent in the year leading up to the fourth quarter of 2013. This aggregate deceleration in global trade includes absolute declines in real trade for many product categories and regions. In the wake of the Great Trade Collapse of 2008–9, understanding of the behavior of trade in slowdowns has improved. Among the many explanations offered for the Great Trade Collapse, including explanations related to uncertainty, trade financing, and new protectionist measures by governments, there has been a significant focus on whether the emergence of global value chains (GVCs) in international trade, and their behavior, are a contributing factor in trade slowdowns.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".