Euro Area Growth Broad-Based in Early 2006
Bibliographic record
Abstract
The global economy continued to look robust at end-2006. In the U.S.A. private consumption increased, notwithstanding the protracted housing slowdown, and the services sector continued to grow at a dynamic pace. In view of the still buoyant economy, a cut in U.S. interest rates does not appear imminent. In Japan, the economic recovery persisted, leading the Bank of Japan to raise interest rates in February 2007 – for the first time since ending six years of zero interest rates in July 2006. In China and Southeast Asia, the rapid pace of growth continued to accelerate. In the euro area, real GDP growth accelerated in the fourth quarter of 2006 and is, moreover, increasingly being driven by domestic demand. The latest forecasts indicate above-potential GDP growth in 2007. Furthermore, the labor market developed favorably, with both the actual and structural unemployment rate down by a significant margin. Since September 2006, the rate of inflation has been below the 2% mark owing to, among other factors, the fall in crude oil prices and the hitherto weak pass-through of the increase in Germany’s VAT rate to consumer prices. In this climate the short-term prospects for price stability have improved as well.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.010 |
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".