Seeking Sustainability: COSA preliminary analysis of sustainability initiatives in the coffee sector
Bibliographic record
Abstract
The growing economic value and consumer popularity of sustainability standards inevitably raise questions about the extent to which their structure and dynamics actually address many environmental, economic and public welfare issues. The COSA (Committee on Sustainability Assessment) project emerged from the concerns of many industry practitioners and the two dozen institutions collectively organized as the Sustainable Coffee Partnership (see Acknowledgements) about the lack of knowledge and dearth of sound scientific inquiry on what actually happens in the process of adopting sustainability initiatives.1 The committee set out to develop a scientifically-credible framework with which to examine and measure the various types of costs and benefits associated with different sustainability approaches. The COSA method is an innovative farm management tool because it incorporates not only economic methods, but also environmental and social metrics to offer a multi-faceted view of sustainability that reflects the intentions and results of the 2002 World Summit on Sustainable Development. The basic COSA approach consists of a data gathering and analysis process so that farmers and other stakeholders can more effectively assess and predict what sort of social, economic and environmental outcomes they may have by implementing different sustainability initiatives. This report covers the initial pilot phase of the COSA project: a process of vetting and testing to prepare the COSA methodology for wider application. Although the primary objective of the testing phase is to identify improvements for making the methodology more suited to diverse producer applications, the opportunity was also taken to compile and analyze the data to demonstrate the analytic capacity and relevance of this work. During testing, the COSA questionnaire was reviewed by the Scientific Committee and external stakeholders prior to being applied in five countries (Kenya, Peru, Costa Rica, Honduras and Nicaragua) across more than 50 farms that represented the most widely-known sustainability initiatives, including Fair Trade, Organic,Utz Certified and Rainforest Alliance. This was followed by several review workshops and basic data compilation and analysis. Data gathered during the testing process do provide a reflection of the actual experience of the specific farms tested and, as such, can provide pointers for a deeper understanding of the functioning of sustainability initiatives in the field.Nevertheless, given the inherent challenge of extracting statistically significant results, the expectation of doing so in the COSA testing process would be unreasonable given the small sample. As such, the data presented by this report must be considered nothing more than observations and NOT firm conclusions or generalizations.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.013 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".