Advancing the Implementation of Connectivity Conservation in Canada: A Case Study of the Policy and Management Environment of the Chignecto Isthmus Region
Bibliographic record
Abstract
Connectivity conservation is a means to enable the unimpeded movement of species and the flow of natural processes to sustain life. Understanding how connectivity conservation functions between parks and protected and conserved areas is a key component of addressing the global biodiversity crisis. The governance and associated policy environment of protected and conserved areas is often complex, and it is challenging for practitioners to understand how connectivity conservation practices can function. In this case study, protected and conserved areas practitioners working in the Chignecto Isthmus region of New Brunswick and Nova Scotia, Canada were interviewed assist in better understanding the successes and challenges of implementing connectivity conservation in a complex interprovincial conservation management environment. Using an organizational readiness framework to analyze implementation of connectivity conservation in the region by understanding the significance of place and time perspectives, community-empowered conditions, and how knowledge is used and shared, the effectiveness of connectivity conservation in the Chignecto Isthmus region was assessed for the successes and challenges that protected and conserved areas practitioners and those associated with connectivity in the region face. This study determined some of the key features of a functioning connectivity conservation system include knowledgeable and committed conservation staff, effective and impactful public outreach and education, and collaborative knowledge sharing among practitioners. Challenges in implementing connectivity conservation included limitation of funding for long-term management strategies and lack of explicit connectivity policy and legislation. This research may serve as a starting point for researchers to understand the diversity of actors and required collaboration that is involved in conservation policy and practices on lands both within and beyond protected areas limits.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.025 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".