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The role of local government in gambling expansion in British Columbia

2005· dissertation· en· W29079083 on OpenAlexaboutno aff
Mario Lee

Bibliographic record

VenueThe Science of The Total Environment · 2005
Typedissertation
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsnot available
FundersDanmarks Tekniske Universitet
KeywordsLocal governmentLimitingPublic administrationRevenuePolitical scienceGovernment (linguistics)Public policyPolitical economyBusinessEconomicsLawFinance

Abstract

fetched live from OpenAlex

This thesis examines the role of local governments in British Columbia in gambling expansion, during the period 1994 to 2004. In particular, it tries to explain why municipalities in BC are able to define gaming policy to an extent unparalleled in Canada and posits three reasons for this: 1) the historical roles of BC municipalities, particularly through the Union of British Columbia Municipalities (UBCM), their province-wide association; 2) the role and influence of charitable organizations, who while defending their interests have struck strategic partnerships with local governments; and 3) the increasing reliance on gaming revenues on the part of provincial governments has required partnerships with local governments. This thesis concludes that while recognizing the limiting constitutional constraints of local governments in Canada, municipalities in British Columbia have nonetheless managed to assert a role in the development of public policy, with gambling policy being a good example of this development.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.193

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0050.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.001

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.

Opus teacher head0.016
GPT teacher head0.284
Teacher spread0.268 · 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 designQualitative
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

Citations1
Published2005
Admission routes1
Has abstractyes

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