The Sustainability of Commercial Tour Operations in Protected Natural Areas: Defining Categories of Environmental Supply
Bibliographic record
Abstract
There is a need in federally protected areas, such as national parks, to investigate the connection between management actions and responsible and sustainable tourism. Environmental supply, as a subset of ecosystem services, is a recent concept that seeks to contribute positively to park management actions about commercial visitor activities and environmental conservation in protected national areas. This can be accomplished by linking commercial visitor demand with understanding of tour operator’s views about environmental supply. This study targets commercial tour operator’s categorization of environmental supply in the Canadian Rocky Mountain national parks of Banff and Jasper. As a concept, environmental supply includes natural features, physical attributes, management initiatives and/or governance policies that influence environmental conservation. Environmental supply, therefore, will include the ecosystems and services of the park destination, visitor education and interpretive programs, zoning and access, environmental impact assessment (EIA) procedures, policies and guidelines, and any other characteristics and initiatives that impact the conservation and/or preservation of nature at a visitor-centered site. How commercial tour operators respond to and manage these for environmental protection in a conservation environment will determine tourism sustainability at the destination. This research presents the results of interviews and a pilot survey that provided information to create initial categories of quality success of environmental supply as defined by commercial tour operators in Banff and Jasper National Parks in the Rocky Mountains of Canada. The goal of this research is to provide a methodology to monitor changes over time by using categories of this research to define quality success indicators of environmental supply that are also parameters of sustainability in high use national parks.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".