MétaCan
Menu
Back to cohort
Record W1550363554 · doi:10.52324/001c.8651

Lots of Bull: Regional Impacts of the 1990s Stock Market Boom

2000· article· en· W1550363554 on OpenAlex
Barney Warf, Joseph C. Cox

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueReview of Regional Studies · 2000
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional Economics and Spatial Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsBoomMetropolitan areaDeregulationStock marketStock (firearms)EconomicsWork (physics)Personal incomeBusinessEconomyGeographyMarket economyEconomic growthEngineering

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.359
Threshold uncertainty score0.810

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.061
GPT teacher head0.269
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it