The SGP in times of financial turbulence and economic crisis
Bibliographic record
Abstract
Introduction The review of the SGP in 2005 was followed by a period of unexpectedly strong economic growth. So much so that most observers were adamant that it was not possible to assess the usefulness of the reformed SGP, given the ‘good times’ and the absence of a ‘bad-weather test’. The situation changed dramatically in the fourth quarter of 2008 when the financial fall-out of the subprime crisis hit home. In less than a few weeks the economic outlook changed from favourable to dire. In other words, as far as the SGP was concerned, the economic circumstances were to move onto uncharted terrain, putting the revised SGP to the test. This chapter offers an overview and an analysis of the period following the review of the SGP up to the financial and economic crisis that came to the fore in the last quarter of 2008. The chapter also offers tentative reflections on possible scenarios for the ongoing developments in 2009. It is structured as follows. The next section contains a concise narrative of the SGP's implementation in the period from 2005 to 2007. The third section summarises the main events of the financial and economic crisis in 2007 and 2008. The fourth section presents an overview of the initial, political response by EU leaders and the Commission by the end of 2008 as well as possible implications for fiscal policy in the EU and thereby for the SGP. It also offers an analysis of these developments, as far as they were known at the time of writing in early 2009, by examining the events through the various theoretical lenses adopted throughout this book, leading to a tentative outlook about what the financial and economic crisis might mean for the future of the SGP.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".