Canadians’ perspectives on how much space nature needs
Bibliographic record
Abstract
Determining how much to set aside in a system of protected areas has been widely discussed. In the past, targets that have been set internationally and domestically are best described as politically driven. In recent years, there has been a call to shift towards evidence-based targets for conservation. One element that has been largely missing from this dialogue is public perception of how much to protect. We conducted an online, regionally balanced survey of just over 2000 Canadians to ask about their values for protected areas, including how much they thought was currently and should be protected. Overall, Canadians overwhelmingly agree that protected areas are necessary and think that approximately 50% of land and sea should be protected in Canada and globally. Nation-wide support for a significant increase in the amount of land/sea protected is a new finding in Canada, although consistent with applications of the same survey in other countries. As the timeline for achieving the current 2020 protected area targets approaches, countries are beginning to discuss what targets to set for the next decade. Our findings demonstrate strong public support for significantly scaling up Canada’s conservation targets, consistent with ecological evidence.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.022 | 0.009 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 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".