Cooperating With “Open Cards”—The Role of Small Intermediary Businesses in Realizing Sustainable International Coffee Supply
Bibliographic record
Abstract
Despite improvements, international food supply in general and coffee supply in particular continue to cause significant greenhouse gas emissions, economic inequities, and negative impacts on human well-being. There is agreement that dominant economic paradigms need to change to comply with the sustainability principles of environmental integrity, economic resilience, and social equity. However, so far, little empirical evidence has been generated to what extent and under which conditions sustainable international coffee supply could be realized through small intermediary businesses such as roasteries, breweries, and/or retailers. This case study reports on a collaborative project between a small coffee brewery and its customers in the U.S. and a small coffee roastery and its suppliers in Mexico that demonstrates how sustainable coffee supply could look like and explores under which conditions it can be realized. A research team facilitated the cooperation using a transdisciplinary research approach, including field visits and stakeholder workshops. The project (i) assessed the sustainability challenges of the current supply and value chains; (ii) developed a vision of a joint sustainable coffee supply chain; (iii) build a strategy to achieve this vision, and (iv) piloted the implementation of the strategy. We discuss the project results against the conditions for sustainable international coffee supply offered in the literature (why they were fulfilled, or not). Overall, the study suggests that small intermediary coffee businesses might have the potential to infuse sustainability across their supply chain if cooperating with “open cards.” The findings confirm some and add some conditions, including economic resilience through cooperation, problem recognition, transparency, trust, and solidarity across the supply chain. The study concludes with reflections on study limitations and future research needs.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 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".