Relational values of nature—a global empirical study of environmental students in 37 countries
Bibliographic record
Abstract
For decades, the question of why people want to protect nature was mostly answered from an instrumental or intrinsic perspective. However, in recent years, a new category of values has received attention: relational values (RVs). Relational values refer to meaningful relationships that people form with nature and with each other through nature, including ethical responsibilities, cultural significance, and identity. They go beyond the dichotomy of intrinsic and instrumental values by highlighting the role of care, stewardship, and responsibility in shaping human–nature relationships. Currently, there is a lack of quantitative empirical studies on the concept of RVs, especially in the international context. This study, therefore, surveyed 4571 environmental students in 37 countries to gain an overview of their RVs. A cluster analysis revealed that there are six overarching global evaluation patterns of RVs, so-called response types, that occur worldwide. The six response types show different characteristics and variations in the agreement of different elements of the RVs. These response types ranged from strong agreement with all relational value items (type 1), to selective endorsement (types 3–6), to broad rejection of RVs (type 2). The correlation of these response types with country-specific wealth indicators showed that the RVs are less pronounced in wealthy countries. This study is the first to carry out a large international comparison of RVs.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".