Whither the Crime in Financial Crises? The Thailand Crisis and the NASDAQ Market Collapse Compared
Bibliographic record
Abstract
The dominant view of what caused the crises in Thailand and elsewhere holds that local corruption in the form of “crony capitalism” is among the prime culprits. This paper seeks to redirect focus away from the alleged crime of commission as a primary cause of recent crises toward the crime of omission in not interrogating more fully both the instability of finance capitalism and the resulting distributional consequences of that instability. A comparison with the recent American experience suggests crises are an enduring feature of capitalism and not the product of “corrupt” Southeast Asian business practices. This comparison suggests as well that redistribution of income over the course of such episodes may very well be quite regressive. Together this perspective suggests that when western interest groups, exercising their influence through the international financial community, advocate for what is in essence a redirection of entitlements, questions of conflict of interest—arguably lying at the heart of the problem with cronyism—must be redirected as well.
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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 | 0.001 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".