Bibliographic record
Abstract
In the third quarter of 2015, the global economy grew by 3,5%. This dropped to 1,9% in the fourth quarter. Weaker economic conditions in China, India and Russia resulted in a sharp decrease in growth in developing economies. Slower growth in the US and Japan resulted in slower growth in developed markets. In the Euro area, growth slowed down slightly towards the end of 2015. According to the European Central Bank, the downside risk to growth in the Euro area has increased. Weaker conditions in emerging markets, increased market volatility and geopolitical risk are the main reasons for the pessimistic outlook. Developing economies are also not expected to perform well. In China, growth moderated to 6,7% in the final quarter of 2015 from the 7,1% achieved in the third quarter. This reflected the rebalancing of the Chinese economy away from investment and manufacturing to consumption. Growth in India plummeted from 10,4% in the third to -1,2% in the fourth quarter of 2015. The recession in Brazil continues.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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 teacher head, 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".