A vernacular for living systems: alternative framings for the future of food
Bibliographic record
Abstract
Industrialized nations face the imminent need to transform our food systems in service to climate, biodiversity, and humanity, and inroads to such transformation are arguably already being made in pockets of innovation and activism around the world. However, debates rage over the various technologies and values that ought to drive those transformations. In this essay I argue that we are in the midst of a paradigm shift in how we think about and design our food systems, away from the industrial paradigm and toward an approach informed by the nature and function of living systems. As a part of that ongoing change, I argue we need to develop a new set of language to replace the familiar industrial values and concepts that underpin how we think about solutions—including scalability, standardization, efficiency, and control. I offer suggestions for alternative concepts drawn from emerging work in the areas if regenerative design, Indigenous stewardship, and complex systems, concepts that can reframe how proponents of food system transformation design and evaluate new ideas and approaches that are more healthful, sustainable, and just.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.034 |
| Scholarly communication | 0.013 | 0.018 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 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".