Risk and Equity Market Weakness: Their Implications for the World Economy
Bibliographic record
Abstract
The terrorist attack on New York on 11 September 2001 caused considerable disruption to the US economy, and especially to the US financial markets. The initial reaction of the financial markets was to increase the discount factor on future profits and reduce future profit projections, and hence stock market valuations fell markedly, as can be seen from charts 1 and 2. This fall has been largely reversed since the attack, but markets have in general continued their decline from their peaks a year or so ago. Falls have been particularly precipitate since July 2001, with the German and French stock market indices falling by 20 per cent over the last three months, whilst the Canadian markets have fallen even more. Stock market falls of the scale we have seen since July are almost bound to impact on the level of economic activity in the major economies. They are likely to reduce the rate of growth of the world economy over the medium term as well as change the structure of saving and investment.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".