People working with nature: a theoretical perspective on the co-production of Nature’s Contributions to People
Bibliographic record
Abstract
The co-production of Nature’s Contributions to People (NCP) is a set of processes in which anthropogenic inputs (i.e. material or non-material actions and the assets supporting these actions) and natural inputs (i.e. ecological structures and processes) interact to produce NCP. An interdisciplinary understanding of NCP co-production can support decision-making on ecosystem management or NCP use, given natural constraints, limited human inputs, possible adverse effects and trade-offs arising from co-production. In this paper, we show that mechanisms of co-production at the ecosystem level and the NCP flow level are fundamentally different. At the level of ecosystems, people manage natural structures and processes to influence the production of potential NCP (e.g. via planting, restoring, fertilizing). At this level, anthropogenic inputs can partially substitute for natural inputs, but natural inputs are necessary whereas anthropogenic inputs are not. At the level of flows, co-production actions convert potential NCP into realized NCP and quality of life (e.g. via harvesting, transporting, transforming, consuming, and appreciating NCP). At this level, anthropogenic inputs are complementary to natural inputs, although some substitutability can occur at the margin. Analysing the substitutability and complementarity between natural and anthropogenic capitals, as well as the adverse effects or mutual enhancement between them, is crucial for informed decision-making on landscape and NCP management. This understanding enables the identification of strategies that can ensure NCP supply and increase human well-being in a sustainable manner.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Science and technology studies Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
| gpt | no category Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".