Lots of Bull: Regional Impacts of the 1990s Stock Market Boom
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
Stock markets in the United States experienced a surge of growth throughout the 1990s as an expanding national economy, deregulation, and demographic change produced the longest bull run in history. This paper explores the reasons for this boom. Next, it charts rising employment in securities and commodities firms, emphasizing the dominant role played by New York. Third, it analyzes the local economic impacts of the bull market using regionalized input-output models of the New York, Los Angeles, and Chicago metropolitan areas to estimate regional output, employment, and personal income effects. In the three combined regions over the years 1991-1999, the bull market generated more than $4.1 billion in output, two-thirds of which was in the securities industry; 136,000 work-years of employment, primarily in producer services; and $8.2 billion in personal income. Geographically, these effects were heavily concentrated in the New York region.
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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 | 0.001 |
| 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 it