A stakeholder-driven approach to building an effective protected area network in Quebec, Canada
Bibliographic record
Abstract
At the Conference of the Parties, in Nagoya (2010), 165 countries ratified the Convention on Biological Conservation, which states that marine and terrestrial protected areas should increase to 10% and 17%, respectively, by 2020. At the Conference, the Quebec government, independent of the Canadian government,decided to align its conservation targets with those ratified in Nagoya and stipulated that 12% of its territory will be under protected area status. Currently, only 9.16% of its territory is officially recognized in the network, and the schedule expires soon. The province of Quebec faces many issues that could make achieving these targets even more difficult: the habitats are highly fragmented; the stakeholders are numerous, with diverse interests within the territory; and the conservation sector has generally prioritized a strict conservation strategy. Considering the high expectations of the government and the short period of time left to achieve its objectives,how will it be possible to reach the Nagoya targets by 2020 while considering the socio-ecological factors? In particular, Quebec needs to expand the range of its conservation tools. A multipurpose protected area status is implementing in the province to achieve socioeconomic as well as conservation goals. Establishment of pilot projects within the territory will help in evaluating the protected area networkʼs adaptation to climate change. Even if they cover only 0.50% of the territory, these multi-purpose protected areas could reach the provincial targets. However, clear indicators for monitoring conservation objectives need to be developed to make sure that multipurpose status achieves ecological goals.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.021 | 0.007 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".