Leveraging Nature‐based Solutions for transformation: Reconnecting people and nature
Bibliographic record
Abstract
Abstract Nature‐based Solutions (NbS) have rapidly been gaining traction across the research, policy and practice spheres, advocated as transformative actions to jointly address biodiversity loss and climate change. However, there are multiple, alternative ways to conceptualize NbS across those three spheres. To inform the NbS discourses in research, policy and practice, we critically reflect on the prevailing framing of NbS. Although the concept links environmental health to human well‐being, we argue that its current dominant framing reinforces a dichotomy between people and nature by highlighting one, external nature working for the benefit of society. For the NbS concept to support transformation, we believe it must embody a reframing of human–nature relationships towards regenerative relationships between humans and nature. To support the transformative aspirations of NbS, we propose a novelcore framingof NbS making explicit the co‐dependence of people and nature, which underpins human well‐being and environmental health. We highlight how such a framing can support a transformation through influencing beliefs and normative values, and second, through the communication and application of the NbS concept in research, policy and practice. We then elaborate on how such a framing is key to support inclusivity and collaboration between diverse research perspectives, policy objectives across scales and implementation practices to deliver just and successful NbS. A free Plain Language Summary can be found within the Supporting Information of this article.
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 | 0.039 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.079 |
| Scholarly communication | 0.018 | 0.021 |
| Open science | 0.002 | 0.025 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".