CASE STUDY -- GUATEMALAN RASPBERRIES AND CYCLOSPORA
Bibliographic record
Abstract
Guatemalan raspberry industry began exporting to the United States in the late 1980s, filling a market niche in the spring and fall when supplies were low.By 1996, Guatemalan raspberry exports were increasing rapidly, up 113 percent from the previous season.That spring and early summer, the U.S. Centers for Disease Control and Prevention (CDC) and Health Canada received reports of more than 1,465 cases of food-borne illness from Cyclospora, a protozoan parasite.Although no one died, the large number of cases generated substantial adverse publicity.Initially, investigators linked the outbreak to California strawberries, but they finally decided that it was associated with Guatemalan raspberries.This case study reviews the efforts to resolve this food safety problem.It is a cautionary tale about the serious impact a food safety outbreak can have on a promising industry.By the time raspberries were identified as the most likely source of contamination, the Guatemalan spring season was over, so the United States took no immediate regulatory action.The U.S. Food and Drug Administration (FDA) and the CDC sent a team of investigators to Guatemala to observe growing conditions.Because Cyclospora was relatively unknown and had never before been associated with raspberries, no one knew which farms or berries were contaminated, how they became contaminated, or how to solve the problem.The Guatemalan Berry Commission (GBC), a growers' organization, responded slowly to the outbreak.Growers came to no consensus on whether there was a problem and were reluctant to accept the FDA's assertion that the contaminated product came from Guatemala, since the claim was based on epidemiology alone with no physical proof.(In fact, the FDA did not find physical evidence of Cyclospora contamination on Guatemalan raspberries until 2000.)Microbial contamination is often low level and sporadic, which makes it difficult to detect.And with perishable produce there is rarely anything left to test by the time an investigation begins.Some growers suspected that the problem was really a trade barrier to protect the U.S. industry from Guatemalan competition.Lack of scientific information compounded the industry's problems in formulating a response.By 1997, the GBC had developed a system to characterize a farm's risk potential: only low-risk farms could export in the spring season.However, the plan had no enforcement mechanism and no traceback system.That spring another large outbreak of food-borne illness in the United States and Canada implicated Guatemalan raspberries.After consulting with the FDA, the GBC voluntarily stopped exporting raspberries to the United States in May 1997.After a second season of contamination problems, both the GBC and the government of Guatemala realized that more
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".