Bibliographic record
Abstract
By combining an economic perspective on financial instability with a sociological analysis of collective behavior, this paper lays out a conceptual foundation that is suggestive of a fuller understanding of speculative manias and financial panics in highly liquid financial assets. The paper argues that a collective enthusiasm develops in an environment of “optimistic uncertainty” created by the gradual diffusion of a revolutionary innovation of the type examined by Rosenberg. An adaptation of Simmel's theory of fashion in the emerging norm framework of Turner and Killian explains the swell of speculative excitement. Once started, the enthusiasm continues in a Schumpeterian manner until the objective potential of the innovation becomes apparent and estimable. If the contemporaneous degree of optimism proves unfounded and prices too high to sustain, a reversal of fortune ushers in distress that may inspire panic. A panic, contrary to implications of extant economic theory, does not necessarily follow a period of extreme speculative enthusiasm. This paper suggests instead, in light of Lang and Lang's analysis of collective dynamics, that certain objective market conditions create a panic in a distressed environment.
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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 | 0.001 | 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 | 0.001 |
| 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".