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Record W193318425

FAIR TRADE COFFEE ENTHUSIASTS SHOULD CONFRONT REALITY

2007· article· en· W193318425 on OpenAlexaboutno aff
Jeremy G. Weber

Bibliographic record

VenueCato Journal · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsnot available
Fundersnot available
KeywordsFair tradeInternational tradeTrade barrierBusinessGeneral partnershipTransparency (behavior)Market accessAgricultureFinancePolitical science
DOInot available

Abstract

fetched live from OpenAlex

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 Cato Journal, Vol. 27, No.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.023
metaresearch head score (Gemma)0.053
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.034
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.053
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0230.044
Scholarly communication0.0310.035
Open science0.0020.016
Research integrity0.0340.041
Insufficient payload (model declined to judge)0.0240.006

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.

Opus teacher head0.053
GPT teacher head0.309
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations50
Published2007
Admission routes1
Has abstractyes

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