Bibliographic record
Abstract
"This book is about the invisible or subtle nature of food and farming, and also about the nature of existence. Everything that we know (and do not know) about the physical world has a subtle counterpart which has been scarcely considered in modernist farming practice and research. If you think this book isn’t for you, if it appears more important to attend to the pressing physical challenges the world is facing before having the luxury of turning to such subtleties, then think again. For it could be precisely this worldview – the one prioritises the physical-material dimension of reality - that helped get us into this situation in the first place. Perhaps we need a different worldview to get us out? This book makes a foundational contribution to the discipline of Subtle Agroecologies, a nexus of indigenous epistemologies, multidisciplinary advances in wave-based and ethereal studies, and the science of sustainable agriculture. Not a farming system in itself, Subtle Agroecologies superimposes a non-material dimension upon existing, materially-based agroecological farming systems. Bringing together 43 authors from 12 countries and five continents, from the natural and social sciences as well as the arts and humanities, this multi-contributed book introduces the discipline, explaining its relevance and potential contribution to the field of Agroecology. Research into Subtle Agroecologies may be described as the systematic study of the nature of the invisible world as it relates to the practice of agriculture, and to do this through adapting and innovating with research methods, in particular with those of a more embodied nature, with the overall purpose of bringing and maintaining balance and harmony. Such research is an open-minded inquiry, its grounding being the lived experiences of humans working on, and with, the land over several thousand years to the present. By reclaiming and reinterpreting the perennial relationship between humans and nature, the implications would revolutionise agriculture, heralding a new wave of more sustainable farming techniques, changing our whole relationship with nature to one of real collaboration rather than control, and ultimately transforming ourselves."
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.835 | 0.798 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".