2013: Breadth of Global Slowdown Disconcerting
Bibliographic record
Abstract
This chapter discusses how the global economy performed in 2013, with the first quarter of 2013 gross domestic product (GDP) growth in the US and China having turned disappointing. Unemployment in Europe remained un-relentlessly brutal, reflecting the deepening recession. In April, an important index of global economic activity fell to its lowest level since October 2012, suggesting that the world economy is barely managing to accelerate. The Organization of Economic Co-operation and Development (OECD) had expressed disappointment that the global economy is moving too slowly, although at multiple speeds, in its recent semiannual Economic Outlook. The International Monetary Fund's (IMF) lowered forecast shaved a quarter of 1 percentage point off its April 2013 projection of 8 percent for China to 7.75 percent, still higher than the government's target of 7.5 percent. China grew at its slowest pace for 13 years in 2012. Latest May data point to unconvincing growth, with momentum losing pace toward a slower second quarter of 2013. It would seem the new leadership could even tolerate growth slipping to 7 percent, provided the economy and employment remain stable.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.035 | 0.009 |
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".