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Record W6926083357 · doi:10.20381/ruor-28892

Gambling on Culture in Canada: Gaming as a Source of Funding for Culture, the Arts and Heritage

2002· other· en· W6926083357 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typeother
Languageen
FieldComputer Science
TopicArtificial Intelligence Applications
Canadian institutionsnot available
Fundersnot available
KeywordsLotteryGovernment (linguistics)LicenseRevenueThe artsStatute

Abstract

fetched live from OpenAlex

This study set out to examine the extent to which cultural activity in Canada is being funded through gaming revenues. It uncovered a tangled web of gaming activities and an even more tangled web of revenue allocations from those activities. Gambling in Canada has been legal since 1969 when an amendment to the Criminal Code gave the provinces authority to operate lottery schemes and casinos and to license charitable and religious organizations to conduct lottery schemes. In 1979, a federal-provincial agreement was entered into whereby the federal government agreed to abstain from conducting and managing lottery schemes. In return, the provinces agreed to pay the federal government the equivalent of C$24 million (in 1979 dollars) annually.

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)0.000
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: Other · Consensus signal: Other
Teacher disagreement score0.457
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.065
GPT teacher head0.300
Teacher spread0.235 · 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

Quick stats

Citations0
Published2002
Admission routes1
Has abstractyes

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