Bibliographic record
Abstract
Over the last two decades, most industrialised and developing countries have experienced episodes of boom and bust in credit markets. These credit cycles often coincided with cycles in economic activity and asset prices. The unwinding of the imbalances built up in the boom has, in some cases, led to severe problems in the financial sector, sometimes culminating in an outright banking crisis. In Japan, the second biggest economy of the world, asset price deflations, both in equity and property, were followed by a decade of financial fragility and deflationary developments in goods prices, with consumer prices falling continuously after 1999.With short-term interest rates having reached the zero lower bound, the country appears to be trapped in a deflationary spiral out of which it finds itself unable to escape. Other South-east Asian countries, such as Hong Kong and Singapore, have also experienced asset price deflations followed by a marked drop in credit creation and goods price deflation in recent years. Some commentators argue that the United States and other industrialised countries are also now, in the wake of the worldwide slump in share prices, on the brink of deflation.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".