Do stakeholders’ values support transformative change in the food system? Evidence from the Netherlands
Bibliographic record
Abstract
Research in the sustainability sciences often emphasizes values and value change as important drivers of sustainability transformations. Drawing from conceptualizations of values developed in environmental psychology and the environmental social sciences, this study offers a survey-based examination of values among stakeholders involved in or close to policymaking processes. The empirical context is the Dutch agri-food system – a hotspot of biodiversity loss, water pollution, greenhouse-gas emissions, and challenges to human and animal health. Based on a survey fielded among stakeholders, including public institutions, researchers, consultancy firms, agribusinesses, and others (n = 174), we investigated the prevalence of environmental and food-system values. Moreover, we asked how food-system values are related to stakeholders’ views on transformative change. Our analysis yields three insights. First, biospheric and altruistic values, often considered in the literature as backbones of a socially and environmentally sustainable food system, were quite strongly endorsed among the surveyed stakeholders. By contrast, egoistic values, which revolve around the cost-benefit calculus of different courses of action irrespective of their environmental or social consequences, received comparatively less endorsement. Second, stakeholders expressed strong agreement with food-system values emphasizing health and community aspects, food and nutrition as a global public good, and ecological and animal-free agriculture, but were less favorable toward values emphasizing technology and markets. Finally, using regression analysis, we show that stakeholders’ food-system values help explain the degree to which they perceive a need for change, and the extent to which they support public policies to make the agri-food system more sustainable.
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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 | 0.008 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".