Ethical Considerations in On-Ground Applications of the Ecosystem Services Concept
Bibliographic record
Abstract
The ecosystem services (ES) concept is one of the main avenues for conveying society's dependence on natural ecosystems. On-ground applications of the concept are now widespread and diverse and include its use as a communication tool, for policy guidance and priority setting, and for designing economic instruments for conservation. Each application raises ethical considerations beyond traditional controversies related to the monetary valuation of nature. We review ethical considerations across major on-ground applications and group them into the following categories: anthropocentric framing, economic metaphor, monetary valuation, commodification, sociocultural impact, changes in motivations, and equity implications. Different applications of the ES concept raise different suites of ethical issues, and we propose methods to address the issues most relevant to each application. We conclude that the ES concept should be considered as only one among various alternative approaches to valuing nature and that reliance on economic metaphors can exclude other motivations for protecting ecosystems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.103 | 0.119 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.054 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.014 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 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".