“Saving the World”, One Fair Trade Cup of Coffee at a Time?
Bibliographic record
Abstract
Coffee is the second-largest globally traded commodity after oil (Murray et al., 2007). As a result, coffee has woven its way into society's social, economic, and political fabric. Unfortunately, the coffee industry has also enabled multiple facets of inequality with negative impacts on its producers because of the volatile nature of its production and markets. To aid in producer equality, the Fair Trade initiative emerged as a social movement to ameliorate the alarmingly high rates of poverty faced by small-scale farmers. Fair Trade attempts to reconfigure capitalist trade relations to ensure fairness within trade relations (Ruiz & Luetchford, 2021, p.885). The overarching objective of this major paper will be to investigate the benefits and limitations of the Fair Trade partnership. A literature review of food movements, specifically food justice, will prove that Fair Trade fits within a reformist political trend that often reproduces, rather than reconfigures, structural inequalities (Ruiz & Luetchford, 2021, p.885). \nThe analysis in the major paper includes a comparison of the coffee industry from the perspective of coffee farmers in Costa Rica, contrasted with Ontario coffee roasters. The Costa Rician small-scale producers are active members of cooperatives and grow coffee as a stable source of income. They shed light on the realities of Fair Trade and working with cooperatives. Understanding the daily realities of producers will be vital in making recommendations on improving Fair Trade policies and practices. The second portion of the analysis will focus on Ontario’s coffee roasters. \nThese individuals operate coffee roasters and work closely with cooperatives to maintain a highly ethical partnership. This research component aims to identify the impact that coffee roasters (in the global North) have on small-scale producers (in the global South). For this major research paper, Ontario’s coffee industry will be limited to coffee roasters who work with Global South cooperatives that sell Fair Trade and other sustainable coffees but not specifically from Costa Rica. \nA consensus gathered from the interviews was that they are all working collectively to make positive changes in the coffee industry. On the producer level, they work with the cooperatives to earn a fair and decent living for their family farm while challenging the injustices at general assemblies. On the coffee roaster side, both Planet Bean and Equator are challenging the status quo by delivering premium coffee and making an actual difference in producers' lives.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.009 | 0.015 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".