Bibliographic record
Abstract
The outlook for world growth this year has deteriorated since April, due to a sharp contraction in world trade in the first quarter of the year and failure to sustain the revival in private sector investment seen in the fourth quarter of 2002. We have as a consequence revised our projections for world growth this year down by ¼ percentage point. This reflects sharp downward revisions of ½–¾ percentage points in the Euro Area and Canada, both of whose exchange rates have continued to appreciate in effective terms, while the outlook for the US and Japan is broadly unchanged. Growth in Japan and the Euro Area stagnated in the first half of 2003, with recessions in Germany, Italy, the Netherlands and Austria appearing likely. The US and Canada, on the other hand, continued to expand, albeit more slowly than in the second half of 2002. Following two years of exceptional weakness, Latin American growth has started to revive, although Venezuela is still suffering from the 2 month stoppage in the oil industry earlier this year and Argentina has lost competitiveness due to a strong appreciation against the dollar. Growth has slowed in several Asian economies, notably South Korea, but China continues to expand rapidly, spurred by the competitiveness impact of the dollar depreciation and infrastructure preparations for the 2008 Olympics. This has helped sustain export growth from the rest of Asia despite the more widespread slowdown in world trade.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.085 | 0.075 |
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".