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Record W2074379351 · doi:10.5367/000000008785633541

The Economics of Regulation and Taxation Policies for Casino Tourism

2008· article· en· W2074379351 on OpenAlexaff
Hasret Benar, Glenn P. Jenkins

Bibliographic record

VenueTourism Economics · 2008
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsQueen's University
Fundersnot available
KeywordsCartelEconomicsInvestment (military)TourismMonopolyProduction (economics)Private sectorPublic economicsMicroeconomicsIncentive

Abstract

fetched live from OpenAlex

A number of states and countries have promoted the development of a casino industry primarily to attract tourists. The policies operated have generally used regulatory or taxation instruments. Such policies may or may not lead to an efficient level of investment and production for the sector. This paper considers four alternative forms of regulatory and taxation policies and examines the interactions between these two sets of investments. The authors find that a turnover tax yields an efficient outcome with a competitive industry and also in the case of a cartel association; but it will be distortionary if a multiplant private monopoly controls the sector. Furthermore, a pure public sector-owned multiplant monopolist is efficient, while a tax on the fixed costs is inefficient if a casino association regulates the sector.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.006
Scholarly communication0.0060.003
Open science0.0010.001
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0090.000

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 head0.077
GPT teacher head0.325
Teacher spread0.248 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2008
Admission routes1
Has abstractyes

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