Scaling up Socially-Oriented Markets:Tipping Point Dynamics in Coupled Supply and Demand Diffusion
Bibliographic record
Abstract
Complex societal challenges, from poverty alleviation to healthy food consumption to ecosystem preservation, have progressively emerged from early -and still persisting- modes of industrialization and consumption that have evolved without consideration for the long-term adverse consequences for either or both the health of the people and that of the planet. Reaching sufficient scale of impact requires to place these considerations upfront as a driver of innovation, profitability and growth in mainstream commercial markets. However, creating such new markets that transform existing social, economic and institutional arrangements is a complex process. In this process numerous practices, ideas and innovations are to be adopted by multiple stakeholders within and across both supply and demand sides of the market, with this coupled adoption posing great challenges. We develop a dynamic computational model that builds on and advances well-known diffusion models. Coupling two sets of stakeholders i.e. these driving supply and demand in the model, we explore the tipping points in widespread adoption of practices based on contextual factors and successful market creation. Besides, we study how diffusion of practices on each side of the market and interactions between two sides facilitate or hinder creation of a new market. Insights from the model enable us to better understand the complexities in creating new markets that need parallel and interconnected adoption of particular practices, and provide policy insights for market-centered interventions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".