World Economy Winter 2018 - Slower growth in the world economy
Bibliographic record
Abstract
World economic growth is moderating accompanied by a broad-based deterioration in economic sentiment. Following a temporary pick up in the second quarter, global activity slowed down significantly in the third quarter and sentiment indicators point towards a further deceleration towards the end of the year. Increased uncertainty from global trade conflicts and the tightening of monetary policy in the US that has put emerging economies under pressure have likely contributed to this development. We expect the global economy to expand at a rate of 3.7 percent this year, followed by 3.4 next year. This is a slight downward revision for 2018 and 2019 by 0.1 percentage points compared to our September forecast. For 2020, we continue to expect world production to increase by 3.4 percent. The escalation of trade conflicts, the possibility of a 'hard Brexit', doubts about the sustainability of Italian public debt, and a delay of reforms in France pose downside risks to our outlook.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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; both teacher heads agree on what is shown here.
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".