Bibliographic record
Abstract
Global economic activity clearly rebounded in the first half of this year. The pick-up from the weakness in the latter half of 2001 was especially marked in North America and Asia, with GDP rising by around 1½ per cent in the first quarter in the United States, Canada and Japan. Activity in Europe was more muted, with GDP rising by 0.3 per cent in the Euro Area and 0.1 per cent in the UK. Although recent monthly data have been mixed, and a number of temporary factors that boosted growth at the turn of the year may have run their course, it appears on balance that there was a further broadly based pick-up in activity in the second quarter of the year. Outside the major industrial economies improving conditions in the IT sector have provided a significant stimulus to some emerging market economies, especially in Asia, but several economies in Latin America have seen a marked deterioration in domestic economic and financial conditions. All told, we expect world GDP growth (measured at purchasing power parities) to be around 2¾ per cent this year, little changed from our previous forecasts. This would be a modest improvement on the growth of 2½ per cent last year, but well below the trend increase of 3½ per cent per annum experienced over the past 30 years.
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 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 | 0.002 |
| 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 | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.083 | 0.068 |
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".