Conservation at a crossroads: governing by global targets, innovative financing, and techno-optimism or radical reform?
Bibliographic record
Abstract
Biodiversity conservation is at a crossroads. A number of trends are converging with the potential to transform our understanding of nature and how we conserve it. First, conservation policy makers are advocating increasingly ambitious global biodiversity targets, such as the agreement to protect 30% of terrestrial, inland water, and of coast and marine areas by 2030 made at the December 2022 Conference of the Parties to the Convention on Biological Diversity. Second, recognizing that governments do not have sufficient resources to reach these ambitious targets, they are turning to private finance and innovative financing mechanisms for help. Third, technological advances are enabling new ways of surveilling people, species, and ecosystems, measuring conservation outcomes, and targeting funding. Finally, long-standing concerns over the alienation of Indigenous Peoples and local communities from land and resources, and the colonial legacy of conservation, have been amplified by widespread contemporary awareness of racism more generally. Nascent critiques of conservation are incorporating but also moving beyond calls for participatory or rights-based approaches to conservation to push for the complete decolonization of conservation, alternatives to capitalist approaches to conservation, and other radical reforms. Collectively, these shifts are both reinforcing traditional conservation practice and power relationships and opening up space to expand understandings of collaborative management, environmental caretaking, and sustainable livelihoods and dramatically reform conservation. In this article, we draw on decades of research studying conservation governance in sites that range from villages to international meetings in order to examine this critical historical moment in conservation politics. We argue that conservation is at an ontological and epistemic moment during which the meaning of biodiversity, how to know it, how to conserve it, and who should conserve it is being fundamentally transformed. As transnational movements seek to transform our political economic system and to decolonize conservation, the consolidation of elite power among actors in finance, technology, governments, and big nongovernmental organizations abstracts conservation from localized contexts, drawing attention away from ensuring effective conservation on the ground and failing to challenge the root causes of biodiversity loss. Thus, continued vigilance is needed to keep equity, rights, justice, and livelihoods at the forefront of conservation.
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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 | 0.016 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.052 |
| Scholarly communication | 0.021 | 0.043 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.009 | 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".