FAIR TRADE COFFEE ENTHUSIASTS SHOULD CONFRONT REALITY
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
From university cafeterias to supermarkets in the developed world, people are buying Fair Trade (FT) coffee certified by the FLO-Cert, the certifying entity of Fairtrade Labelling Organizations International (FLO).The assumption is that such purchases will contribute to the welfare of marginalized producers in the developing world.While sales of FT coffee in Europe have stabilized, the North American and Japanese markets are growing rapidly.Total sales increased 40 percent from 2004 to 2005, to a total volume of 33,992 metric tons (MT) (FTO 2005).What is "Fair Trade"?According to FINE, the umbrella organization that comprises the four largest Fair Trade organizations (FLO, International Federation for Alternative Trade, Network of European World Shops, and the European Fair Trade Association), Fair Trade is a trading partnership, based on dialogue, transparency and respect, that seeks greater equity in international trade.It contributes to sustainable development by offering better trading conditions to, and securing the rights of, marginalized producers and workers-especially in the South [FINE 2001].The FINE definition optimistically assumes that the trading partnerships and conditions promoted by Fair Trade necessarily "contribute to sustainable development."It is true that the Fair Trade coffee system-the producers, exporters, importers, and retailers operating by the rules and standards of FLO-has improved living standards for many participating coffee growers (Bacon 2005, Raynolds 2004).Yet the system faces vexing issues such as a disconnect between promotional materials and reality, excess supply, and the marginalization of
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 it