It's all in that plate of food: An Interview with Carolyn Steel
Bibliographic record
Abstract
Although it might seem that the problem of feeding big cities has been solved, it has come at a heavy costecological destruction, climate crisis, resource depletion, record obesity rates and rising hungerjeopardizing sustainable development.Furthermore, despite interacting with a number of urban systems, food systems have been disregarded by urban planners until recently, while the distance between consumers and producers increases.Food, however, holds great potential to become the medium through which we pursue a better life and more sustainable cities.In this interview, the British architect Carolyn Steel explores the historical and future connections between humans, cities and food, the current challenges we face in this realm and the possible solutions embedded in her idea of Sitopiafrom the Greek words for 'food' (sitos) and 'place' (topos)as an approach that could be used to retrofit existing cities, design new ones, and rethink our everyday relationship with the food on our plates.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.007 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.009 | 0.018 |
| Insufficient payload (model declined to judge) | 0.009 | 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".