The Universal Precautionary Principle: New Pillars and Pathways for Environmental, Sociocultural, and Economic Resilience
Bibliographic record
Abstract
Global environmental degradation is linked to a worldwide erosion of ethnic identity and cultural diversity, as well as market disruption. Cultures rely heavily on the local environment around them, and local communities play a key role in conserving natural resources. People’s identity, connection with land, and the adaptation of Indigenous and local knowledge are prerequisites for resilience. Though the Environmental Precautionary Principle (EPP) aims to tackle environmental degradation by privileging the environment in the face of uncertainty, it is not sufficient on its own; it does not take into account the intimate connection between nature and local culture, nor does it prioritize community or cultural wellbeing. We suggest expanding this concept into a multi-faceted Universal Precautionary Principle (UPP), which recognizes people’s connection to the land, and elevates community, cultural, and economic wellbeing as equally important values alongside environmental concerns. Here, we coin the Universal Precautionary Principle, outline its four core pillars—systems, governance, diversity, and resilience—and introduce its three subsets: Environmental Precautionary Principle, Sociocultural Precautionary Principle, and Economic Precautionary Principle. We discuss potential outcomes of its application, and offer operational guidelines to implement the Universal Precautionary Principle in practice, before concluding that it is a crucial tool to build environmental, sociocultural, and economic resilience. In essence, reciprocity is the keystone for continuance—if the environment is healthy, people are more likely to be healthy. Equally, if people are healthy, the environment is more likely to be healthy; for both people and the environment to be healthy, their culture and economy must be healthy.
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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 | 0.018 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.075 |
| Scholarly communication | 0.011 | 0.020 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.006 | 0.009 |
| 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".