Not Just Small Potatoes: Cultural Entrepreneurship in the Moralizing of Markets
Bibliographic record
Abstract
While there is a growing literature on moral markets that aim to create social value through market exchange, much of it has focused on how producer activism is able to legitimate new, institutionally complex, organizational and economic forms that are inscribed with competing market and social/community logics. Much less attention has been directed towards understanding how moral markets are scaled by the entry of large, established organizations. While the scaling of moral markets entails the risk of conservative goal transformation, we still know relatively little about how moral values become embedded in markets, providing an ongoing catalyst for social value creation. Based on a five-year ethnographic study, we show how cultural entrepreneurship associated with the creation of a cross-sector partnership, legitimated local food procurement by large, established organizations, enabling the scaling of the overall market. We argue that a key aspect of their success had to do with bridging the institutional void segregating local and industrial food logics. Based on our study, we highlight how this institutional void bridging was facilitated by cultural entrepreneurship that initially focused on communications that decoupled the values and practices associated with the local food logic, and subsequently, reinfused locavore values by valorizing stories and activities that recoupled those values to food procurement practices after the institutional void was diminished. We discuss the implications of our study for research on moral markets and cultural entrepreneurship.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.026 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".