Financial bubbles and their magic: asset price as a heroic journey in the financial markets
Bibliographic record
Abstract
Why do financial crises appear unprecedented in spite of being a rather regular occurrence across countries and time? There are many answers from various schools of finance and economics, including Minsky’s financial instability hypothesis in which systemic stability endogenously results in instability. We explore the inclusion of observed human behavior in an endogenous framework by engaging with anthropological concepts such as myth, ritual and magic that structure and explain our behaviour, and by extending the concept of agency from human to non-human. We also point to the possibility of better understanding our position in the mythological cycle using the new social media data. The aim of the article is to offer a holistic framework of interpretation of causes and circumstances of economic crises, using the tools of economy, semiotics, and economic anthropology that would account for both the universality of these crises and for their particular occurrences that always seem unique.
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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 | 0.002 | 0.008 |
| 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 | 0.019 |
| Scholarly communication | 0.006 | 0.014 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".