Fiscal implications of moving to tourism finance for parks: Ontario Provincial Parks
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".