Weak Investment in the EU: A Long-Term Cross-Sectoral Phenomenon
Bibliographic record
Abstract
Based on capital stock, in total, over six trillion euros less was invested in the European Union between 1999 and 2007 than in the non-European OECD countries, including the US, Canada, and Japan. In the euro area, investment was more than 7.5 trillion euros less than in non-European OECD countries. In virtually all EU member states, gross fixed assets (capital stock) are older than the OECD average and also demonstrate slower growth. This is particularly true for industry, which is expected to play a key role in Europe's recovery. In order to achieve a higher growth rate, Europe must tackle this lack of investment across the board. Just implement investment programs in individual countries, such as the southern European crisis countries is not enough. In order to launch a broad investment offensive across the EU as a whole, specific steps must be taken. With a view to tackling the lack of investment in the long term, measures include an efficient competition policy and investmentfriendly tax policy.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.011 |
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".