Ecosystem services: A new framework for old ideas, or advancing environmental decision‐making? Learning from Canadian forerunners to the ES concept
Bibliographic record
Abstract
Frameworks of ecosystem services (ES) are promoted as a new and important way to recognize, understand, and account for nature's benefits. We questioned assertions of the novelty of ES ideas and conducted a comparative analysis of approaches in planning, landscape architecture, and sustainable forest management against the Millennium Ecosystem Assessment ES framework. We conclude that the newer Millennium Ecosystem Assessment ES framing may assist planners in connecting local land‐use change to human well‐being, assessing trade‐offs, and accounting for future uncertainty. Analogous approaches such as sustainable forest management offer practical insights, for example, about gauging, guiding, and reporting on sustainable use of ecosystems. We encourage environmental planners to engage with ES researchers to develop the approach and advance planning practice.
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 | 0.026 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.014 | 0.064 |
| Scholarly communication | 0.017 | 0.021 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.013 |
| 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".