Food for Tomorrow: Navigating Moral Tensions in Sustainable Market Transformation
Bibliographic record
Abstract
This symposium showcases four papers on traditional and novel food contexts that examine how organizations navigate tensions between growth, innovation, and moral integrity in pursuit of sustainable food system transformation. Drawing on diverse settings—ranging from farmers' markets, to bean-to-bar chocolate production, to cultivated meat, to plant-based alternatives—this symposium explores the interplay between markets, morality, and sustainability. Collectively, the presentations shed light on diverse, but interrelated themes, including how organizations manage authenticity and legitimacy while scaling; how market evolution shapes and is shaped by morality; and how the pursuit of sustainability drives the emergence of novel organizational forms and practices. Taken together, this symposium aims to engage scholars in a productive dialogue about transforming food systems for the future. From Movement to Market? Struggles over the Meaning of Local Food at Farmers’ Markets Author: Yoojin Lee; McGill University Author: Robert J. David; McGill University Crafting an Organizational Form: Insights from Bean-to-Bar Chocolate Production Author: Jo-Ellen Pozner; Santa Clara University Author: Jennifer Woolley; Santa Clara University Beyond Good and Bad: The Co-Evolution of Technology and Morality in Cultivated Meat Author: Magdalena Winkler; Vienna University of Economics and Business Author: Giuseppe Delmestri; Mainstreaming Moral Markets: Dynamics of Consistency Between Category Positioning and Expectations Author: Cristian Arlex Trejos Taborda; Università della Svizzera Italiana
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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.030 |
| Scholarly communication | 0.015 | 0.012 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| 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".