A World of Chance: Betting on Religion, Games, Wall Street
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although financial markets often try to distance themselves from gambling, the two factors have far more in common than usually thought. When, historically, there were no financial institutions such as banks, lotteries constituted the ways by which expensive items were disposed of, and governments raised money quickly. Gambling tables fulfilled roles that venture capital and banking do today. 'Gamblers' created clearinghouses and sustained liquidity. When those gamblers bet on price distributions in futures markets, they were redefined as 'speculators'. Today they are called 'hedge fund managers' or 'bankers'. Though the names have changed, the actions undertaken have essentially stayed the same. This book shows how discussion on 'chance', 'risk', 'gambling', 'insurance', and 'speculation' illuminates where societies stood, where we are today, and where we may be heading
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.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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 it