ORI GIN AL PA PER The Effect of Recessions on Gambling Expenditures
Bibliographic record
Abstract
The Author(s) 2011. This article is published with open access at Springerlink.com Abstract This article examines the influence of the business cycle on expenditures of three major types of legalized gambling activities: Casino gambling, lottery, and pari-mutuel wagering. Empirical results are obtained using monthly aggregated US per capita consumption time series for the period 1959.01–2010.08. Among the three gambling activities only lottery consumption appears to be recession-proof. This series is charac-terized by a vast and solid growth that exceeds the growth in income and the growth in other gambling sectors. Casino gambling expenditures show a positive growth during expansions and no growth during recessions. Hence, the loss in income during recessions affects casino gambling. However, income shocks which are not directly related to the business cycle do not influence casino gambling expenditures. Pari-mutuel wagering dis-plays an overall negative trend and its average growth rate is smaller than the growth in income, especially during recessions. The findings of this article provide important implications for the gambling industry and for local governments.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".