Analysis of Food Safety Management Systems in the Beef Meat Processing and Distribution Chain in Uganda
Bibliographic record
Abstract
Meat production is an essential component in food security and the economy in Uganda. However, food safety concerns pose a challenge to public health in Uganda and impede access to regional and global markets. Here, food safety management (FSM) practices in the Ugandan beef supply chain were evaluated. A cross-sectional survey was conducted in major slaughterhouses (n = 3), butcher shops (n = 184), and supermarkets (n = 25) in Uganda’s capital, Kampala. The three slaughterhouses had low scores in core control and assurance activities of FSM. Packaging interventions were weak in all the slaughterhouses, while only one slaughterhouse had a functional cooling facility. Supermarkets implemented better hygienic and preventative practices in comparison to butcher shops. However, both sourced from slaughterhouses that had low-to-poor hygiene practices, which weakened the efforts implemented in the supermarkets. Furthermore, most butcher shops did not offer training to meat handlers on HACCP (Hazard Analysis and Critical Control Point)-based practices. The low food safety performance in the supply chain was primarily attributed to poor sanitation, hygiene, and handling practices. Therefore, HACCP-based training and robust preventive, intervention, and monitoring systems are needed in the Ugandan beef supply chain to benefit public health and increase competitiveness.
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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 | 0.001 |
| 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) | 0.000 | 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 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".