Voyages to Kitchi Gami: The Lake Superior National Marine Conservation Area and Regional Tourism Opportunities in Canada's First National Marine Conservation Area
Bibliographic record
Abstract
With a substantial amount of natural (e.g., islands, estuaries, shoals) and cultural (e.g., pictographs, lighthouses, shipwrecks) heritage, the Lake Superior National Marine Conservation Area (LSNMCA), located in Northwestern Ontario, is a protected area steeped in history. Apart from a few exceptions, this region of Ontario has lacked the opportunity to capitalize on potential tourism and recreational opportunities. An historic overview of the region highlights past tourism achievements, such as brook trout fishing in the Nipigon River, and the Rossport Fish Derby, and indicates new tourism opportunities in Northwestern Ontario (e.g., sailing regattas and kayak symposia). The significance of tourism in a region largely dependent upon mining and forestry is also highlighted. The article then reviews the potential role of the LSNMCA in regional tourism development by utilizing Kelleher's levels of stakeholder engagement framework. Although stakeholder involvement in the LSNMCA, according to Kelleher's model, requires further work, the establishment of this protected area (the very first of its kind in Canada) appears to be engaging stakeholders in regional tourism development.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".