The contribution of stewardship to park planning and management in Ontario: A study of Bruce Peninsula and Georgian Bay Islands national parks
Bibliographic record
Abstract
Parks Canada has adopted ecosystem-based management as a means of maintaining ecological integrity. However, ecosystems often extend beyond park boundaries. Where parks share boundaries with other government-protected areas, arrangements have often been made for cooperation. These arrangements usually result in mutual benefits for the protected areas involved. Where parks share boundaries with privately owned land, stewardship is one of the methods being used to implement conservation-based practices. This study investigated the extent to which stewardship contributes to park planning and management in Ontario using the Georgian Bay Islands and Bruce Peninsula National Parks as case studies. Results show that stewardship is being practiced in the parks' greater ecosystem. The main tools used to encourage and implement stewardship were education, conservation easements and property acquisition. The impact of these tools was reduced by issues which include the general theme of educational messages, limited funds for property acquisition, and uncoordinated property acquisition between the Non Government Organisations. The parks are involving the local community in park planning and management but in a rather limited way, with Georgian Bay Islands National Park offering less opportunity for involvement than Bruce Peninsula National Park. This implies that the contribution of stewardship to park management is still limited. If these two parks are to benefit from stewardship in the long run, attitudes have to be pro-conservation and management practices in the greater park ecosystem have to be complementary to the parks' goal of maintaining ecological integrity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".