An environmental justice perspective on ecosystem services
Bibliographic record
Abstract
Mainstreaming of ecosystem service approaches has been proposed as one path toward sustainable development. Meanwhile, critics of ecosystem services question if the approach can account for the multiple values of ecosystems to diverse groups of people, or for aspects of inter- and intra-generational justice. In particular, an ecosystem service approach often overlooks power dimensions and capabilities that are core to environmental justice. This article addresses the need for greater guidance on incorporating justice into ecosystem services research and practice. We point to the importance of deep engagement with stakeholders and rights holders to disentangle contextual factors that moderate justice outcomes on ecosystem service attribution and appropriation in socio-political interventions. Such a holistic perspective enables the integration of values and knowledge plurality for enhancing justice in ecosystem services research. This broadened perspective paves a way for transformative ecosystem service assessments, management, and research, which can help inform and design governance structures that nourish human agency to sustainably identify, manage, and enjoy ecosystem services for human wellbeing.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.033 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".