The role of soils in learning and inspiration, physical and psychological experiences, and in supporting identities
Bibliographic record
Abstract
This paper reviews the literature on soil and nature's contributions to people (NCP) around learning and inspiration, physical and psychological experiences, and supporting identities, revealing a range of relationships to imagining, understanding and experiencing soil. Often labelled elsewhere as 'cultural ecosystem services', these NCP provide a range of benefits that are mostly non-material, non-consumptive and intangible. The review finds that NCP framings help to highlight how soils have contributed to inspiring learning and creative works, like art; to mental and physical health benefits, such as through recreation and gardening; and to cultural identities and practices, including religious practices and efforts for social justice. Overall, soils have played a large role in human creative endeavours, are the root of significant relationships to the environment and can be conceptualized through key metaphors, ideas and theory as a bridge linking culture and nature together. Yet despite the wide-ranging contributions of soils to these NCP, the literature remains uneven and much more remains to be understood, including how relational values of care and stewardship with soils can be fostered and how attention to the co-produced 'biosocial' nature of soil can help improve practices for soil health. This article is part of the theme issue 'The role of soils in delivering Nature's Contributions to People'.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".