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Record W2103187541 · doi:10.1177/155862350600100405

Addressing the Small Market Problem for Canadian NHL Franchises: On-site Gaming as a New Revenue Stream

2006· article· en· W2103187541 on OpenAlex
Daniel S. Mason

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Sport Finance · 2006
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSports Analytics and Performance
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRevenue sharingSubsidyRevenueOrder (exchange)Context (archaeology)BusinessGovernment (linguistics)LeagueFinanceMarketingEconomicsMarket economy

Abstract

fetched live from OpenAlex

This paper identifies the unique problems faced by Canadian small market (CSM) franchises in the National Hockey League (NHL). While featuring characteristics similar to other major leagues in North America, CSM franchises are also burdened by currency and taxation issues that favor US-based teams, as well as a reliance on gate revenues, which have exacerbated the problem for NHL teams. Three general alternatives devised to address the small market problem are introduced in this paper: (1) allow other stakeholders, such as levels of government, to subsidize weaker teams; (2) create revenue sharing agreements among teams to distribute money to weaker franchises; and (3) create artificial restraints on player salaries in order to reduce the ability of large market teams to stockpile talent (Cocco & Jones, 1997). These are reviewed in the context of the NHL and include the Mills Report and Manley proposals, the Alberta Players Tax, lotteries, revenue sharing, and salary caps. A proposal is put forward to explore the use of on-site gaming in arenas in order to provide additional revenues for Canadian-based NHL teams. The benefits of such a proposal are then reviewed, which include: (1) acting as a less regressive tax than other government subsidies by targeting game attendees; (2) having fans who already support the team provide the subsidization, eliminating those who are not followers of hockey from bearing the financial burden; and (3) enhancing the viewing experience of fans. In doing so, it is hoped that an alternative way of assisting small market Canadian teams can be achieved that does not require substantial legal or labor negotiations, while not altering the structural characteristics of the league as a whole.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.587
Threshold uncertainty score0.974

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)0.0000.000

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 head0.042
GPT teacher head0.248
Teacher spread0.205 · 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