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Record W1979119857 · doi:10.1111/ecaf.12093

Ticket Scalping as a Means of Managing Risk

2014· article· en· W1979119857 on OpenAlex
Vincent Geloso

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

VenueEconomic Affairs · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSports Analytics and Performance
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsTicketBusinessSubsidyEconomicsComputer securityMarket economyComputer science

Abstract

fetched live from OpenAlex

Abstract Ticket scalping (known as touting in the UK ) is often criticised for raising prices to consumers and producing unjustified profits. Conventional economic theory, however, shows that ticket scalping allows tickets to be reallocated in a more optimal manner with regard to the utility of consumers. This article points to an additional benefit from ticket scalping: by providing a secondary market it acts as a potentially powerful tool of risk management for event organisers. It is argued that curtailing ticket scalping may in the long run lead to a decline in the supply of privately provided events and concerts, especially lesser‐known ones. This in turn may stimulate a demand for public subsidy.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.679
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.002

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.

Opus teacher head0.010
GPT teacher head0.193
Teacher spread0.183 · 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