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Record W2141053791 · doi:10.1080/13606719.2013.849503

Fiscal implications of moving to tourism finance for parks: Ontario Provincial Parks

2013· article· en· W2141053791 on OpenAlex
Paul F.J. Eagles

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

VenueManaging Leisure · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTourismGovernment (linguistics)Fiscal yearBusinessDiversity (politics)Public financeAgricultural economicsEconomicsFinanceEconomic growthGeographyPolitical science

Abstract

fetched live from OpenAlex

This article reviews the fiscal implications of moving from government funding of park management to user-funded operations in a major park system, the Provincial Parks in Ontario, Canada. In 1995/1996 after the introduction of the new funding model, the government grant to Ontario Parks was reduced to $10.6 million from $28.8 million, a reduction of 63%. Over the 15-year study-period from 1995 to 2010, the tourism-based income increased from $18.1 million to $64.9 million, an increase of 257%, while visitation increased from 8.6 million to 9.5 million in the same period, an increase of 10%. The total operating budget of Ontario Parks increased from $28.2 million to $76.5 million, an increase of 165%. The park tourism income increased through: (1) increased levels of fees charged; (2) increased diversity of pricing; and (3) broadening the income to include new features. Factors leading to the successful utilization of this user pay system for a park system are suggested.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.998

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 head0.041
GPT teacher head0.209
Teacher spread0.168 · 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