Evidence-based decision-making in Canada’s protected areas organizations: Implications for management effectiveness
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Aichi Biodiversity Target 19 calls on Parties to the United Nations Convention on Biological Diversity (CBD) to improve, share, transfer, and apply knowledge. In this study, we provide an initial assessment of the state of evidence-based decision-making in Canada’s protected areas organizations by examining (1) the value and use of various forms of evidence by managers and (2) the extent to which institutional conditions enable or inhibit the use of evidence in decision-making. Results revealed that although managers value and use many forms of evidence in their decision-making, information produced by staff and their organizations are given priority. Other forms of evidence, such as Indigenous knowledge and peer-reviewed information, are valued and used less. The most significant barriers to evidence-based decision-making were limited financial resources, lack of staff, inadequate timeframes for decision-making, a lack of monitoring programs, and a disconnect between researchers and decision-makers. Overall, our results suggest that the potential benefits of evidence-based approaches are not being maximized in Canada’s protected areas organizations. We propose several recommendations to introduce or improve the use of diverse forms of evidence to enhance management effectiveness of Canada’s protected areas and by extension conservation outcomes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it