Communities in transition: changing views on tourism development as a vehicle for economic diversification in Northern Ontario, Canada.
Bibliographic record
Abstract
In recent years, an increasing number of protected areas have been established as an attempt to preserve the biodiversity of coastal and terrestrial ecosystems. In Canada, government agencies have set a goal to increase the number of protected areas by establishing more national/provincial parks, marine protected areas (MPAs), national wildlife areas, marine wildlife areas, and migratory bird sanctuaries. Many of these protected areas are being created in rural areas where there is a heavy dependence on natural resources for survival. Recently in Ontario the first National Marine Conservation Area (NMCA) was established on the North Shore of Lake Superior. Due to recent global changes that have affected the resource-based economy in Canada, many rural communities have turned to developing their tourism attributes to diversify their economy. The purpose of this case study is to examine how community stakeholders‘ views toward tourism have changed over the course of the development of the Lake Superior National Marine Conservation Area (LSNMCA). Findings indicated that since the LSNMCA initiative was first introduced, local attitudes have positively changed toward the potential of tourism development in the area; such shifts coincide with the decline and restructuring of the region‘s resource-based industries. Keywords: protected areas, tourism, rural and resource-based communities, Lake Superior National Marine Conservation Area (LSNMCA)
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".