Understanding and avoiding misplaced efforts in conservation
Bibliographic record
Abstract
Conservation relies on cooperation among different interest groups and appropriate use of evidence to make decisions that benefit people and biodiversity. However, misplaced conservation occurs when cooperation and evidence are impeded by polarization and misinformation. This impedance influences actions that directly harm biodiversity, alienate partners and disrupt partnerships, waste resources, misinform the public, and (or) delegitimize evidence. As a result of these actions, misplaced conservation outcomes emerge, making it more difficult to have positive outcomes for biodiversity. Here we describe cases where a failed appreciation for cooperation, evidence, or both have eroded efforts to conserve biodiversity. Generally, these case studies illustrate that averting misplaced conservation requires greater adherence to processes that elevate the role of evidence in decision-making and that place collective, long-term benefits for biodiversity over the short-term gains of individuals or groups. Efforts to integrate human dimensions, cooperation, and evidence into conservation will increase the efficacy and success of efforts to conserve global biodiversity while benefiting humanity.
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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 | 0.078 | 0.148 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.008 | 0.055 |
| Scholarly communication | 0.018 | 0.022 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 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".