Bibliographic record
Abstract
The downturn in global economic activity that started in 2008 was turned into a major recession after the failure of Lehman Brothers in September 2008. It appears that world output fell by more than 1 per cent in 2009, and OECD output probably fell by around 3½ per cent. The effects on output were more marked in the Euro Area and the UK than they were in the US or Canada, which partly reflects the policy responses chosen by Treasuries and Central Banks. The financial crisis that drove the recession affected banks in the US, the UK, the Euro Area and the rest of Europe rather more than it did those in Canada, Australia and Japan. However, recessions have been common, with only Australia and Poland appearing to avoid them. The financial crisis led rapidly to a freezing of trade credit, which caused world trade to decline very sharply at the beginning of 2009. The financial crisis also led to an increase in risk premia in investment decision-making and hence to a decline in the equilibrium capital output ratio, which caused a sharp reduction in the demand for capital goods. Combined with credit rationing effects for firms needing access to borrowing, this induced a collapse in investment. Trade channels made the crisis global, as did movements in exchange rates. Interest rates were cut sharply in the US, Europe and Japan, and approached levels seen in Japan for the previous decade. As a result the yen appreciated strongly, and the combination of the effects of this appreciation on competitiveness and the decline in investment goods trade meant that Japan suffered worse than most other countries, at least in the short term.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.011 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 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 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".